kernel_ridge_regression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load necessary modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from sklearn.metrics import pairwise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generate training data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "N=31\n",
    "\n",
    "X_train = np.zeros((N*N,2))\n",
    "X_1, X_2 = np.meshgrid(np.linspace(-4,4,N),np.linspace(-4,4,N))\n",
    "X_train[:,0] = X_1.flatten()\n",
    "X_train[:,1] = X_2.flatten()\n",
    "y_train = np.zeros(N*N)\n",
    "y_train = y_train.reshape(-1,1)\n",
    "\n",
    "def f(x, y):\n",
    "     return (np.sin(np.sqrt((0.5*x) ** 2 + (0.5*y) ** (4))))\n",
    "\n",
    "y_train =  f(X_train[:,0],X_train[:,1])\n",
    "y_train = y_train.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Train kernel-based model (without regularization)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# of inputs/features:  961\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phi_X_train = pairwise.rbf_kernel(X_train, X_train,gamma=0.15)\n",
    "print('# of inputs/features: ', phi_X_train.shape[1])\n",
    "\n",
    "lin = LinearRegression()\n",
    "lin.fit(phi_X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Evaluate model also outside of training data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "N_eval = 150\n",
    "x_1 = np.linspace(-4.2,4.2,N_eval)\n",
    "x_2 = np.linspace(-4.2,4.2,N_eval)\n",
    "X_1, X_2 = np.meshgrid(x_1,x_2)\n",
    "X_eval = np.zeros((N_eval**2,2))\n",
    "X_eval[:,0] = X_1.flatten()\n",
    "X_eval[:,1] = X_2.flatten()\n",
    "phi_X_eval = pairwise.rbf_kernel(X_eval, X_train,gamma=0.15)\n",
    "\n",
    "Y_eval = lin.predict(phi_X_eval)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot training data and model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        return MozWebSocket;\n",
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       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
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       "mpl.figure.prototype._init_header = function() {\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
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       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
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       "\n",
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       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
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       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
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       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
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       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
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       "        mouse_event_fn(event);\n",
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       "    this.rubberband = rubberband;\n",
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       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
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       "        // Keep the size of the canvas, canvas container, and rubber band\n",
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       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
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       "    this._resize_canvas(600, 600);\n",
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       "        canvas_div.focus();\n",
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       "\n",
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       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
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       "        return fig.toolbar_button_onclick(event['data']);\n",
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       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
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       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos = np.empty(X_1.shape + (2,))\n",
    "pos[:, :, 0] = X_1; pos[:, :, 1] = X_2\n",
    "fig = plt.figure()\n",
    "ax = fig.gca(projection='3d')\n",
    "ax.scatter(X_train[:,0], X_train[:,1],y_train[:],c='red', label=\"training set\")\n",
    "ax.plot_surface(X_1,X_2,Y_eval.reshape(N_eval,N_eval), label=\"regression predictor\")\n",
    "ax.set_xlabel('$X_1$')\n",
    "ax.set_ylabel('$X_2$')\n",
    "ax.set_zlabel(\"$\\hat{Y}$\")\n",
    "ax.view_init(elev=8., azim=-18)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Train kernel-based model with ridge regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# of inputs/features:  961\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Ridge(alpha=0.001)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phi_X_train = pairwise.rbf_kernel(X_train, X_train,gamma=0.15)\n",
    "print('# of inputs/features: ', phi_X_train.shape[1])\n",
    "\n",
    "lin = Ridge(0.001)\n",
    "lin.fit(phi_X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Evaluate model also outside of training data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "N_eval = 150\n",
    "x_1 = np.linspace(-4.2,4.2,N_eval)\n",
    "x_2 = np.linspace(-4.2,4.2,N_eval)\n",
    "X_1, X_2 = np.meshgrid(x_1,x_2)\n",
    "X_eval = np.zeros((N_eval**2,2))\n",
    "X_eval[:,0] = X_1.flatten()\n",
    "X_eval[:,1] = X_2.flatten()\n",
    "phi_X_eval = pairwise.rbf_kernel(X_eval, X_train,gamma=0.15)\n",
    "\n",
    "Y_eval = lin.predict(phi_X_eval)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot training data and model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos = np.empty(X_1.shape + (2,))\n",
    "pos[:, :, 0] = X_1; pos[:, :, 1] = X_2\n",
    "fig = plt.figure()\n",
    "ax = fig.gca(projection='3d')\n",
    "ax.scatter(X_train[:,0], X_train[:,1],y_train[:],c='red', label=\"training set\")\n",
    "ax.plot_surface(X_1,X_2,Y_eval.reshape(N_eval,N_eval), label=\"regression predictor\")\n",
    "ax.set_xlabel('$X_1$')\n",
    "ax.set_ylabel('$X_2$')\n",
    "ax.set_zlabel(\"$\\hat{Y}$\")\n",
    "ax.view_init(elev=8., azim=-18)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}