Decision tree.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Imports necesarios\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sb\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from sklearn import tree\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from IPython.display import Image as PImage\n",
    "from subprocess import check_call\n",
    "from PIL import Image, ImageDraw, ImageFont\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (16, 9)\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>artist</th>\n",
       "      <th>mood</th>\n",
       "      <th>tempo</th>\n",
       "      <th>genre</th>\n",
       "      <th>artist_type</th>\n",
       "      <th>chart_date</th>\n",
       "      <th>durationSeg</th>\n",
       "      <th>top</th>\n",
       "      <th>anioNacimiento</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Small Town Throwdown</td>\n",
       "      <td>BRANTLEY GILBERT featuring JUSTIN MOORE &amp; THOM...</td>\n",
       "      <td>Brooding</td>\n",
       "      <td>Medium Tempo</td>\n",
       "      <td>Traditional</td>\n",
       "      <td>Male</td>\n",
       "      <td>20140628</td>\n",
       "      <td>191.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1975.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Bang Bang</td>\n",
       "      <td>JESSIE J, ARIANA GRANDE &amp; NICKI MINAJ</td>\n",
       "      <td>Energizing</td>\n",
       "      <td>Medium Tempo</td>\n",
       "      <td>Pop</td>\n",
       "      <td>Female</td>\n",
       "      <td>20140816</td>\n",
       "      <td>368.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1989.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Timber</td>\n",
       "      <td>PITBULL featuring KE$HA</td>\n",
       "      <td>Excited</td>\n",
       "      <td>Medium Tempo</td>\n",
       "      <td>Urban</td>\n",
       "      <td>Mixed</td>\n",
       "      <td>20140118</td>\n",
       "      <td>223.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1993.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Sweater Weather</td>\n",
       "      <td>THE NEIGHBOURHOOD</td>\n",
       "      <td>Brooding</td>\n",
       "      <td>Medium Tempo</td>\n",
       "      <td>Alternative &amp; Punk</td>\n",
       "      <td>Male</td>\n",
       "      <td>20140104</td>\n",
       "      <td>206.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1989.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>MIRANDA LAMBERT</td>\n",
       "      <td>Yearning</td>\n",
       "      <td>Medium Tempo</td>\n",
       "      <td>Traditional</td>\n",
       "      <td>Female</td>\n",
       "      <td>20140301</td>\n",
       "      <td>232.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                 title  \\\n",
       "0   0  Small Town Throwdown   \n",
       "1   1             Bang Bang   \n",
       "2   2                Timber   \n",
       "3   3       Sweater Weather   \n",
       "4   4             Automatic   \n",
       "\n",
       "                                              artist        mood  \\\n",
       "0  BRANTLEY GILBERT featuring JUSTIN MOORE & THOM...    Brooding   \n",
       "1              JESSIE J, ARIANA GRANDE & NICKI MINAJ  Energizing   \n",
       "2                            PITBULL featuring KE$HA     Excited   \n",
       "3                                  THE NEIGHBOURHOOD    Brooding   \n",
       "4                                    MIRANDA LAMBERT    Yearning   \n",
       "\n",
       "          tempo               genre artist_type  chart_date  durationSeg  top  \\\n",
       "0  Medium Tempo         Traditional        Male    20140628        191.0    0   \n",
       "1  Medium Tempo                 Pop      Female    20140816        368.0    0   \n",
       "2  Medium Tempo               Urban       Mixed    20140118        223.0    1   \n",
       "3  Medium Tempo  Alternative & Punk        Male    20140104        206.0    0   \n",
       "4  Medium Tempo         Traditional      Female    20140301        232.0    0   \n",
       "\n",
       "   anioNacimiento  \n",
       "0          1975.0  \n",
       "1          1989.0  \n",
       "2          1993.0  \n",
       "3          1989.0  \n",
       "4             0.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Cargamos los datos\n",
    "artists_billboard = pd.read_csv(r\"artists_billboard_fix3.csv\")\n",
    "artists_billboard.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "top\n",
       "0    494\n",
       "1    141\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Visualizamos la cantidad de canciones que son top\n",
    "artists_billboard.groupby('top').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x157d2644688>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualizamos la cantidad de generos musicales\n",
    "sb.catplot('genre',data=artists_billboard,kind=\"count\", aspect=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x157d2f86308>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualizamos la cantidad año de nacimiento por artista\n",
    "sb.catplot('anioNacimiento',data=artists_billboard,kind=\"count\", aspect=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Mapeo de los datos\n",
    "\n",
    "# Mood Mapping \n",
    "artists_billboard['moodEncoded'] = artists_billboard['mood'].map( {'Energizing': 6, \n",
    "                                        'Empowering': 6,\n",
    "                                        'Cool': 5, \n",
    "                                        'Yearning': 4, # anhelo, deseo, ansia\n",
    "                                        'Excited': 5, #emocionado\n",
    "                                        'Defiant': 3, \n",
    "                                        'Sensual': 2, \n",
    "                                        'Gritty': 3, #coraje \n",
    "                                        'Sophisticated': 4,\n",
    "                                        'Aggressive': 4, # provocativo\n",
    "                                        'Fiery': 4, #caracter fuerte\n",
    "                                        'Urgent': 3, \n",
    "                                        'Rowdy': 4, #ruidoso alboroto\n",
    "                                        'Sentimental': 4,\n",
    "                                        'Easygoing': 1, # sencillo\n",
    "                                        'Melancholy': 4, \n",
    "                                        'Romantic': 2, \n",
    "                                        'Peaceful': 1, \n",
    "                                        'Brooding': 4, # melancolico\n",
    "                                        'Upbeat': 5, #optimista alegre\n",
    "                                        'Stirring': 5, #emocionante\n",
    "                                        'Lively': 5, #animado\n",
    "                                        'Other': 0,'':0} ).astype(int)\n",
    "# Tempo Mapping \n",
    "artists_billboard['tempoEncoded'] = artists_billboard['tempo'].map( {'Fast Tempo': 0, 'Medium Tempo': 2, 'Slow Tempo': 1, '': 0} ).astype(int)\n",
    "# Genre Mapping \n",
    "artists_billboard['genreEncoded'] = artists_billboard['genre'].map( {'Urban': 4, \n",
    "                                          'Pop': 3, \n",
    "                                          'Traditional': 2, \n",
    "                                          'Alternative & Punk': 1,\n",
    "                                         'Electronica': 1, \n",
    "                                          'Rock': 1, \n",
    "                                          'Soundtrack': 0, \n",
    "                                          'Jazz': 0,\n",
    "                                          'Other':0,'':0} \n",
    "                                       ).astype(int)\n",
    "# artist_type Mapping \n",
    "artists_billboard['artist_typeEncoded'] = artists_billboard['artist_type'].map( {'Female': 2, 'Male': 3, 'Mixed': 1, '': 0} ).astype(int)\n",
    "\n",
    "\n",
    "# Mapping Song Duration\n",
    "artists_billboard.loc[ artists_billboard['durationSeg'] <= 150, 'durationEncoded']                          = 0\n",
    "artists_billboard.loc[(artists_billboard['durationSeg'] > 150) & (artists_billboard['durationSeg'] <= 180), 'durationEncoded'] = 1\n",
    "artists_billboard.loc[(artists_billboard['durationSeg'] > 180) & (artists_billboard['durationSeg'] <= 210), 'durationEncoded'] = 2\n",
    "artists_billboard.loc[(artists_billboard['durationSeg'] > 210) & (artists_billboard['durationSeg'] <= 240), 'durationEncoded'] = 3\n",
    "artists_billboard.loc[(artists_billboard['durationSeg'] > 240) & (artists_billboard['durationSeg'] <= 270), 'durationEncoded'] = 4\n",
    "artists_billboard.loc[(artists_billboard['durationSeg'] > 270) & (artists_billboard['durationSeg'] <= 300), 'durationEncoded'] = 5\n",
    "artists_billboard.loc[ artists_billboard['durationSeg'] > 300, 'durationEncoded'] = 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Nuevo conjunto de datos para construir el árbol\n",
    "drop_elements = ['id','title','artist','mood','tempo','genre','artist_type','chart_date','anioNacimiento','durationSeg']\n",
    "artists_encoded = artists_billboard.drop(drop_elements, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">top</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "      <th>sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>artist_typeEncoded</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.305263</td>\n",
       "      <td>95</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.320261</td>\n",
       "      <td>153</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.162791</td>\n",
       "      <td>387</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         top          \n",
       "                        mean count sum\n",
       "artist_typeEncoded                    \n",
       "1                   0.305263    95  29\n",
       "2                   0.320261   153  49\n",
       "3                   0.162791   387  63"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Genero del artista contra canciones en el top\n",
    "artists_encoded[['artist_typeEncoded', 'top']].groupby(['artist_typeEncoded'], as_index=False).agg(['mean', 'count', 'sum'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">top</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>count</th>\n",
       "      <th>sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genreEncoded</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.105263</td>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.070000</td>\n",
       "      <td>100</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.008850</td>\n",
       "      <td>113</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.319149</td>\n",
       "      <td>188</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.330233</td>\n",
       "      <td>215</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   top          \n",
       "                  mean count sum\n",
       "genreEncoded                    \n",
       "0             0.105263    19   2\n",
       "1             0.070000   100   7\n",
       "2             0.008850   113   1\n",
       "3             0.319149   188  60\n",
       "4             0.330233   215  71"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Genero musical contra canciones en el top\n",
    "artists_encoded[['genreEncoded', 'top']].groupby(['genreEncoded'], as_index=False).agg(['mean', 'count', 'sum'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Max Depth  Average Accuracy\n",
      "         1          0.556101\n",
      "         2          0.556101\n",
      "         3          0.623710\n",
      "         4          0.617460\n",
      "         5          0.618973\n",
      "         6          0.606250\n"
     ]
    }
   ],
   "source": [
    "# Validando niveles para el árbol\n",
    "cv = KFold(n_splits=10) # Numero deseado de \"folds\" que haremos\n",
    "accuracies = list()\n",
    "max_attributes = len(list(artists_encoded))\n",
    "depth_range = range(1, max_attributes + 1)\n",
    "\n",
    "# Testearemos la profundidad de 1 a cantidad de atributos +1\n",
    "for depth in depth_range:\n",
    "    fold_accuracy = []\n",
    "    tree_model = tree.DecisionTreeClassifier(criterion='entropy',\n",
    "                                             min_samples_split=20,\n",
    "                                             min_samples_leaf=5,\n",
    "                                             max_depth = depth,\n",
    "                                             class_weight={1:3.5})\n",
    "    for train_fold, valid_fold in cv.split(artists_encoded):\n",
    "        f_train = artists_encoded.loc[train_fold] \n",
    "        f_valid = artists_encoded.loc[valid_fold] \n",
    "\n",
    "        model = tree_model.fit(X = f_train.drop(['top'], axis=1), \n",
    "                               y = f_train[\"top\"]) \n",
    "        valid_acc = model.score(X = f_valid.drop(['top'], axis=1), \n",
    "                                y = f_valid[\"top\"]) # calculamos la precision con el segmento de validacion\n",
    "        fold_accuracy.append(valid_acc)\n",
    "\n",
    "    avg = sum(fold_accuracy)/len(fold_accuracy)\n",
    "    accuracies.append(avg)\n",
    "    \n",
    "# Mostramos los resultados obtenidos\n",
    "df = pd.DataFrame({\"Max Depth\": depth_range, \"Average Accuracy\": accuracies})\n",
    "df = df[[\"Max Depth\", \"Average Accuracy\"]]\n",
    "print(df.to_string(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Visualización del árbol\n",
    "# Crear arrays de entrenamiento y las etiquetas que indican si llegó a top o no \n",
    "y_train = artists_encoded['top']\n",
    "x_train = artists_encoded.drop(['top'], axis=1).values \n",
    "\n",
    "# Crear Arbol de decision con profundidad = 3\n",
    "decision_tree = tree.DecisionTreeClassifier(criterion='entropy',\n",
    "                                            min_samples_split=20,\n",
    "                                            min_samples_leaf=5,\n",
    "                                            max_depth = 3,\n",
    "                                            class_weight={1:3.5})\n",
    "decision_tree.fit(x_train, y_train)\n",
    "\n",
    "# exportar el modelo a archivo .dot\n",
    "with open(r\"tree1.dot\", 'w') as f:\n",
    "     f = tree.export_graphviz(decision_tree,\n",
    "                              out_file=f,\n",
    "                              max_depth = 7,\n",
    "                              impurity = True,\n",
    "                              feature_names = list(artists_encoded.drop(['top'], axis=1)),\n",
    "                              class_names = ['No', 'N1 Billboard'],\n",
    "                              rounded = True,\n",
    "                              filled= True )\n",
    "        \n",
    "# Convertir el archivo .dot a png para poder visualizarlo\n",
    "check_call(['dot','-Tpng',r'tree1.dot','-o',r'tree1.png'], shell=True)\n",
    "PImage(\"tree1.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "63.94\n"
     ]
    }
   ],
   "source": [
    "#Precisión\n",
    "acc_decision_tree = round(decision_tree.score(x_train, y_train) * 100, 2)\n",
    "print(acc_decision_tree)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Probabilidad de Acierto: 67.26%\n"
     ]
    }
   ],
   "source": [
    "#Predicciones\n",
    "#predecir artista CAMILA CABELLO featuring YOUNG THUG\n",
    "# con su canción Havana llego a numero 1 Billboard US en 2017\n",
    "\n",
    "x_test = pd.DataFrame(columns=('top','moodEncoded', 'tempoEncoded', 'genreEncoded','artist_typeEncoded','durationEncoded'))\n",
    "x_test.loc[0] = (1,5,2,4,1,3)\n",
    "y_pred = decision_tree.predict(x_test.drop(['top'], axis = 1))\n",
    "y_proba = decision_tree.predict_proba(x_test.drop(['top'], axis = 1))\n",
    "print(\"Probabilidad de Acierto: \" + str(round(y_proba[0][y_pred][0]* 100, 2))+\"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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