mixtcomp-titanic-example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RMixtComp: Titanic example\n",
    "Unsupervised classification with mixed and missing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: RMixtCompUtilities\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(RMixtComp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preparation\n",
    "Import the Titanic dataset included in the package. A `tittanic` dataframe is then available, with 1309 observations and 8 variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>pclass</th><th scope=col>survived</th><th scope=col>sex</th><th scope=col>age</th><th scope=col>sibsp</th><th scope=col>parch</th><th scope=col>fare</th><th scope=col>embarked</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1st</td><td>1</td><td>female</td><td>29.0</td><td>0</td><td>0</td><td>211.3375</td><td>S </td></tr>\n",
       "\t<tr><th scope=row>16</th><td>1st</td><td>0</td><td>male  </td><td>  NA</td><td>0</td><td>0</td><td> 25.9250</td><td>S </td></tr>\n",
       "\t<tr><th scope=row>38</th><td>1st</td><td>1</td><td>male  </td><td>  NA</td><td>0</td><td>0</td><td> 26.5500</td><td>S </td></tr>\n",
       "\t<tr><th scope=row>169</th><td>1st</td><td>1</td><td>female</td><td>38.0</td><td>0</td><td>0</td><td> 80.0000</td><td>NA</td></tr>\n",
       "\t<tr><th scope=row>285</th><td>1st</td><td>1</td><td>female</td><td>62.0</td><td>0</td><td>0</td><td> 80.0000</td><td>NA</td></tr>\n",
       "\t<tr><th scope=row>1226</th><td>3rd</td><td>0</td><td>male  </td><td>60.5</td><td>0</td><td>0</td><td>      NA</td><td>S </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & pclass & survived & sex & age & sibsp & parch & fare & embarked\\\\\n",
       "  & <fct> & <fct> & <fct> & <dbl> & <int> & <int> & <dbl> & <fct>\\\\\n",
       "\\hline\n",
       "\t1 & 1st & 1 & female & 29.0 & 0 & 0 & 211.3375 & S \\\\\n",
       "\t16 & 1st & 0 & male   &   NA & 0 & 0 &  25.9250 & S \\\\\n",
       "\t38 & 1st & 1 & male   &   NA & 0 & 0 &  26.5500 & S \\\\\n",
       "\t169 & 1st & 1 & female & 38.0 & 0 & 0 &  80.0000 & NA\\\\\n",
       "\t285 & 1st & 1 & female & 62.0 & 0 & 0 &  80.0000 & NA\\\\\n",
       "\t1226 & 3rd & 0 & male   & 60.5 & 0 & 0 &       NA & S \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 8\n",
       "\n",
       "| <!--/--> | pclass &lt;fct&gt; | survived &lt;fct&gt; | sex &lt;fct&gt; | age &lt;dbl&gt; | sibsp &lt;int&gt; | parch &lt;int&gt; | fare &lt;dbl&gt; | embarked &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| 1 | 1st | 1 | female | 29.0 | 0 | 0 | 211.3375 | S  |\n",
       "| 16 | 1st | 0 | male   |   NA | 0 | 0 |  25.9250 | S  |\n",
       "| 38 | 1st | 1 | male   |   NA | 0 | 0 |  26.5500 | S  |\n",
       "| 169 | 1st | 1 | female | 38.0 | 0 | 0 |  80.0000 | NA |\n",
       "| 285 | 1st | 1 | female | 62.0 | 0 | 0 |  80.0000 | NA |\n",
       "| 1226 | 3rd | 0 | male   | 60.5 | 0 | 0 |       NA | S  |\n",
       "\n"
      ],
      "text/plain": [
       "     pclass survived sex    age  sibsp parch fare     embarked\n",
       "1    1st    1        female 29.0 0     0     211.3375 S       \n",
       "16   1st    0        male     NA 0     0      25.9250 S       \n",
       "38   1st    1        male     NA 0     0      26.5500 S       \n",
       "169  1st    1        female 38.0 0     0      80.0000 NA      \n",
       "285  1st    1        female 62.0 0     0      80.0000 NA      \n",
       "1226 3rd    0        male   60.5 0     0           NA S       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data(titanic)\n",
    "titanic[c(1, 16, 38, 169, 285, 1226),]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>pclass</dt><dd>0</dd><dt>survived</dt><dd>0</dd><dt>sex</dt><dd>0</dd><dt>age</dt><dd>263</dd><dt>sibsp</dt><dd>0</dd><dt>parch</dt><dd>0</dd><dt>fare</dt><dd>1</dd><dt>embarked</dt><dd>2</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[pclass] 0\n",
       "\\item[survived] 0\n",
       "\\item[sex] 0\n",
       "\\item[age] 263\n",
       "\\item[sibsp] 0\n",
       "\\item[parch] 0\n",
       "\\item[fare] 1\n",
       "\\item[embarked] 2\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "pclass\n",
       ":   0survived\n",
       ":   0sex\n",
       ":   0age\n",
       ":   263sibsp\n",
       ":   0parch\n",
       ":   0fare\n",
       ":   1embarked\n",
       ":   2\n",
       "\n"
      ],
      "text/plain": [
       "  pclass survived      sex      age    sibsp    parch     fare embarked \n",
       "       0        0        0      263        0        0        1        2 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colSums(is.na(titanic))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Refactor categorical variables to MixtComp format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic$sex <- refactorCategorical(titanic$sex, c(\"male\", \"female\"), c(1, 2))\n",
    "titanic$pclass <- refactorCategorical(titanic$pclass, c(\"1st\", \"2nd\", \"3rd\"), c(1, 2, 3))\n",
    "titanic$embarked <- refactorCategorical(titanic$embarked, c(\"C\", \"Q\", \"S\"), c(1, 2, 3))\n",
    "titanic$survived <- refactorCategorical(titanic$survived, c(0, 1), c(1, 2))\n",
    "titanic[is.na(titanic)] = \"?\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>pclass</th><th scope=col>survived</th><th scope=col>sex</th><th scope=col>age</th><th scope=col>sibsp</th><th scope=col>parch</th><th scope=col>fare</th><th scope=col>embarked</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1</td><td>2</td><td>2</td><td>29  </td><td>0</td><td>0</td><td>211.3375</td><td>3</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>1</td><td>1</td><td>1</td><td>?   </td><td>0</td><td>0</td><td>25.925  </td><td>3</td></tr>\n",
       "\t<tr><th scope=row>38</th><td>1</td><td>2</td><td>1</td><td>?   </td><td>0</td><td>0</td><td>26.55   </td><td>3</td></tr>\n",
       "\t<tr><th scope=row>169</th><td>1</td><td>2</td><td>2</td><td>38  </td><td>0</td><td>0</td><td>80      </td><td>?</td></tr>\n",
       "\t<tr><th scope=row>285</th><td>1</td><td>2</td><td>2</td><td>62  </td><td>0</td><td>0</td><td>80      </td><td>?</td></tr>\n",
       "\t<tr><th scope=row>1226</th><td>3</td><td>1</td><td>1</td><td>60.5</td><td>0</td><td>0</td><td>?       </td><td>3</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & pclass & survived & sex & age & sibsp & parch & fare & embarked\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <chr> & <int> & <int> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\t1 & 1 & 2 & 2 & 29   & 0 & 0 & 211.3375 & 3\\\\\n",
       "\t16 & 1 & 1 & 1 & ?    & 0 & 0 & 25.925   & 3\\\\\n",
       "\t38 & 1 & 2 & 1 & ?    & 0 & 0 & 26.55    & 3\\\\\n",
       "\t169 & 1 & 2 & 2 & 38   & 0 & 0 & 80       & ?\\\\\n",
       "\t285 & 1 & 2 & 2 & 62   & 0 & 0 & 80       & ?\\\\\n",
       "\t1226 & 3 & 1 & 1 & 60.5 & 0 & 0 & ?        & 3\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 8\n",
       "\n",
       "| <!--/--> | pclass &lt;dbl&gt; | survived &lt;dbl&gt; | sex &lt;dbl&gt; | age &lt;chr&gt; | sibsp &lt;int&gt; | parch &lt;int&gt; | fare &lt;chr&gt; | embarked &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| 1 | 1 | 2 | 2 | 29   | 0 | 0 | 211.3375 | 3 |\n",
       "| 16 | 1 | 1 | 1 | ?    | 0 | 0 | 25.925   | 3 |\n",
       "| 38 | 1 | 2 | 1 | ?    | 0 | 0 | 26.55    | 3 |\n",
       "| 169 | 1 | 2 | 2 | 38   | 0 | 0 | 80       | ? |\n",
       "| 285 | 1 | 2 | 2 | 62   | 0 | 0 | 80       | ? |\n",
       "| 1226 | 3 | 1 | 1 | 60.5 | 0 | 0 | ?        | 3 |\n",
       "\n"
      ],
      "text/plain": [
       "     pclass survived sex age  sibsp parch fare     embarked\n",
       "1    1      2        2   29   0     0     211.3375 3       \n",
       "16   1      1        1   ?    0     0     25.925   3       \n",
       "38   1      2        1   ?    0     0     26.55    3       \n",
       "169  1      2        2   38   0     0     80       ?       \n",
       "285  1      2        2   62   0     0     80       ?       \n",
       "1226 3      1        1   60.5 0     0     ?        3       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic[c(1, 16, 38, 169, 285, 1226),]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "set.seed(42)\n",
    "titanic$age[sample(which(titanic$age < 10), 20)] = \"[0:10]\"\n",
    "titanic$fare[sample(which(titanic$fare > 200), 20)] = \"[200:+inf]\"\n",
    "titanic$age[sample(which(titanic$age < 10), 20)] = \"[0:10]\"\n",
    "titanic$embarked[sample(which(titanic$embarked == 3), 40)] = \"{2, 3}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "model <- list(fare = \"Gaussian\", age = \"Gaussian\",\n",
    "              pclass = \"Multinomial\", survived = \"Multinomial\",\n",
    "              sex = \"Multinomial\", embarked = \"Multinomial\",\n",
    "              sibsp = \"Poisson\", parch = \"Poisson\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "====== Run MixtComp in learn mode with 5 run(s) per number of classes and 2 core(s)\n",
      "Data: 1309 individuals and 8 variables.\n",
      "-- K = 1\n",
      "Run completed in 1.221s\n",
      "-- K = 2\n",
      "Run completed in 0.928s\n",
      "-- K = 3\n",
      "Run completed in 1.177s\n",
      "-- K = 4\n",
      "Run completed in 1.322s\n",
      "-- K = 5\n",
      "Run completed in 1.459s\n",
      "-- K = 6\n",
      "Run completed in 1.54s\n",
      "-- K = 7\n",
      "Run completed in 1.649s\n",
      "-- K = 8\n",
      "Run completed in 1.86s\n",
      "-- K = 9\n",
      "Run completed in 1.979s\n",
      "-- K = 10\n",
      "Run completed in 2.022s\n",
      "-- K = 11\n",
      "Run completed in 2.04s\n",
      "-- K = 12\n",
      "Run completed in 2.436s\n",
      "-- K = 13\n",
      "Run completed in 2.358s\n",
      "-- K = 14\n",
      "Run completed in 2.73s\n",
      "-- K = 15\n",
      "Run completed in 2.947s\n",
      "-- K = 16\n",
      "Run completed in 3.749s\n",
      "-- K = 17\n",
      "Run completed in 4.787s\n",
      "-- K = 18\n",
      "Run completed in 5.315s\n",
      "-- K = 19\n",
      "Run completed in 6.19s\n",
      "-- K = 20\n",
      "Run completed in 6.67s\n",
      "Total runtime: 54.383s\n",
      "Best model according to BIC: 13 clusters.\n"
     ]
    }
   ],
   "source": [
    "res <- mixtCompLearn(titanic, model, nClass = 1:20, nRun = 5, nCore = 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Output analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "############### MixtCompLearn Run ###############\n",
      "nClass: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 \n",
      "Criterion used: BIC \n",
      "            1         2         3         4         5         6         7\n",
      "BIC -18067.89 -16136.58 -15825.82 -15004.10 -14839.08 -14742.83 -14657.59\n",
      "ICL -18067.89 -16175.85 -15881.76 -15092.17 -14906.92 -14846.53 -14740.87\n",
      "            8         9        10        11        12        13        14\n",
      "BIC -14571.47 -14522.24 -14478.12 -14456.52 -14519.19 -14417.63 -14442.51\n",
      "ICL -14691.30 -14696.01      -Inf -14604.00 -14716.05      -Inf -14583.56\n",
      "           15        16        17        18        19        20\n",
      "BIC -14490.68 -14470.08 -14423.24 -14512.19 -14513.35 -14545.62\n",
      "ICL      -Inf      -Inf      -Inf      -Inf -14712.48      -Inf\n",
      "Best model: 13 clusters \n",
      "########### MixtComp Run ###########\n",
      "Number of individuals: 1309 \n",
      "Number of variables: 8 \n",
      "Number of clusters: 13 \n",
      "Mode: learn \n",
      "Time: 0.618 s\n",
      "SEM burn-in iterations done: 50/50 \n",
      "SEM run iterations done: 50/50 \n",
      "Observed log-likelihood: -13814.76 \n",
      "BIC: -14417.63 \n",
      "ICL: -Inf \n",
      "Discriminative power:\n",
      "    fare   pclass      sex    sibsp    parch survived embarked      age \n",
      "   0.610    0.411    0.183    0.178    0.171    0.166    0.146    0.131 \n",
      "Proportions of the mixture:\n",
      "0.172 0.052 0.125 0.056 0.077 0.074 0.176 0.061 0.051 0.016 0.042 0.067 0.03 \n",
      "Parameters of the most discriminant variables:\n",
      "- fare: Gaussian \n",
      "         mean     sd\n",
      "k: 1   13.806  5.041\n",
      "k: 2   27.957  1.910\n",
      "k: 3    7.827  0.734\n",
      "k: 4   37.210 15.764\n",
      "k: 5   23.260  8.720\n",
      "k: 6   74.999 26.227\n",
      "k: 7    7.845  0.120\n",
      "k: 8   32.969 25.664\n",
      "k: 9  191.545 56.381\n",
      "k: 10 512.329  0.082\n",
      "k: 11  66.076 19.689\n",
      "k: 12  12.511  1.389\n",
      "k: 13  27.159  8.831\n",
      "- pclass: Multinomial \n",
      "      modality 1 modality 2 modality 3\n",
      "k: 1       0.000      0.063      0.937\n",
      "k: 2       1.000      0.000      0.000\n",
      "k: 3       0.000      0.000      1.000\n",
      "k: 4       0.000      0.000      1.000\n",
      "k: 5       0.000      1.000      0.000\n",
      "k: 6       0.968      0.032      0.000\n",
      "k: 7       0.000      0.000      1.000\n",
      "k: 8       0.417      0.329      0.254\n",
      "k: 9       1.000      0.000      0.000\n",
      "k: 10      0.238      0.238      0.524\n",
      "k: 11      1.000      0.000      0.000\n",
      "k: 12      0.000      1.000      0.000\n",
      "k: 13      0.000      1.000      0.000\n",
      "- sex: Multinomial \n",
      "      modality 1 modality 2\n",
      "k: 1       0.481      0.519\n",
      "k: 2       0.836      0.164\n",
      "k: 3       1.000      0.000\n",
      "k: 4       0.537      0.463\n",
      "k: 5       0.117      0.883\n",
      "k: 6       0.000      1.000\n",
      "k: 7       0.687      0.313\n",
      "k: 8       1.000      0.000\n",
      "k: 9       0.445      0.555\n",
      "k: 10      0.619      0.381\n",
      "k: 11      1.000      0.000\n",
      "k: 12      1.000      0.000\n",
      "k: 13      1.000      0.000\n",
      "####################################\n"
     ]
    }
   ],
   "source": [
    "summary(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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B0agh2AQyDYATSBNrjX+/hD2jt7iLHsiqPSZ56jdy80+4dmpXwmlnhwOvrAdHRn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h/G4ZLijsesZf/cbdbkCza+wCGu96bz9/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\nGEM9sLOlGCmsELmk3y0alivIgp/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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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EkiJB9C0ghJIiQfQtIISSIkH0LSCEki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\n290muQtLl5PrypSQmmHp8Q7PLdh3yOrf7vZM//PGx+5cVrr8nDu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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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8dbv3tFfI8UI75Hsmv875E2znwpDNtn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\nupwbPrS93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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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qrnTw8bNmw4fvz4Cy+84G7Jzc2V72knn/M8fvy43O5wOC5cuBAbGzts2LBhw4a9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\nYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "$criteria\n",
       "\n",
       "$discrimPowerVar\n",
       "\n",
       "$proportion\n",
       "\n",
       "$fare\n",
       "\n",
       "$pclass\n",
       "\n",
       "$sex\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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48ePSqEqK2t1el0BoMhPDw8MTExIiIiIiIiJiYmPj4+KCio0aKNN6I+G6alixcv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\npVjcxKOPPipJ0qlTp5zdCATh4+Pz2muvdT5taGh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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MjIiIuL69ixoxCisrJSpVIZX/L29rbdVAEAQNvRrVs3mUyWn59fr67T6fR6vWml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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Dht2rTyUl1JSUlxWTT9ZgAAeECV+UfTYrE4uy4IoWmwO3Xq1IkTJ1555RWTyeTm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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "heatmapVar(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A matrix: 8 × 8 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>fare</th><th scope=col>age</th><th scope=col>pclass</th><th scope=col>survived</th><th scope=col>sex</th><th scope=col>embarked</th><th scope=col>sibsp</th><th scope=col>parch</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>fare</th><td>1.00</td><td>0.38</td><td>0.40</td><td>0.37</td><td>0.36</td><td>0.39</td><td>0.37</td><td>0.37</td></tr>\n",
       "\t<tr><th scope=row>age</th><td>0.38</td><td>1.00</td><td>0.62</td><td>0.75</td><td>0.74</td><td>0.74</td><td>0.72</td><td>0.74</td></tr>\n",
       "\t<tr><th scope=row>pclass</th><td>0.40</td><td>0.62</td><td>1.00</td><td>0.60</td><td>0.58</td><td>0.60</td><td>0.56</td><td>0.57</td></tr>\n",
       "\t<tr><th scope=row>survived</th><td>0.37</td><td>0.75</td><td>0.60</td><td>1.00</td><td>0.81</td><td>0.74</td><td>0.71</td><td>0.73</td></tr>\n",
       "\t<tr><th scope=row>sex</th><td>0.36</td><td>0.74</td><td>0.58</td><td>0.81</td><td>1.00</td><td>0.72</td><td>0.71</td><td>0.73</td></tr>\n",
       "\t<tr><th scope=row>embarked</th><td>0.39</td><td>0.74</td><td>0.60</td><td>0.74</td><td>0.72</td><td>1.00</td><td>0.69</td><td>0.71</td></tr>\n",
       "\t<tr><th scope=row>sibsp</th><td>0.37</td><td>0.72</td><td>0.56</td><td>0.71</td><td>0.71</td><td>0.69</td><td>1.00</td><td>0.73</td></tr>\n",
       "\t<tr><th scope=row>parch</th><td>0.37</td><td>0.74</td><td>0.57</td><td>0.73</td><td>0.73</td><td>0.71</td><td>0.73</td><td>1.00</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 8 × 8 of type dbl\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & fare & age & pclass & survived & sex & embarked & sibsp & parch\\\\\n",
       "\\hline\n",
       "\tfare & 1.00 & 0.38 & 0.40 & 0.37 & 0.36 & 0.39 & 0.37 & 0.37\\\\\n",
       "\tage & 0.38 & 1.00 & 0.62 & 0.75 & 0.74 & 0.74 & 0.72 & 0.74\\\\\n",
       "\tpclass & 0.40 & 0.62 & 1.00 & 0.60 & 0.58 & 0.60 & 0.56 & 0.57\\\\\n",
       "\tsurvived & 0.37 & 0.75 & 0.60 & 1.00 & 0.81 & 0.74 & 0.71 & 0.73\\\\\n",
       "\tsex & 0.36 & 0.74 & 0.58 & 0.81 & 1.00 & 0.72 & 0.71 & 0.73\\\\\n",
       "\tembarked & 0.39 & 0.74 & 0.60 & 0.74 & 0.72 & 1.00 & 0.69 & 0.71\\\\\n",
       "\tsibsp & 0.37 & 0.72 & 0.56 & 0.71 & 0.71 & 0.69 & 1.00 & 0.73\\\\\n",
       "\tparch & 0.37 & 0.74 & 0.57 & 0.73 & 0.73 & 0.71 & 0.73 & 1.00\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 8 × 8 of type dbl\n",
       "\n",
       "| <!--/--> | fare | age | pclass | survived | sex | embarked | sibsp | parch |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| fare | 1.00 | 0.38 | 0.40 | 0.37 | 0.36 | 0.39 | 0.37 | 0.37 |\n",
       "| age | 0.38 | 1.00 | 0.62 | 0.75 | 0.74 | 0.74 | 0.72 | 0.74 |\n",
       "| pclass | 0.40 | 0.62 | 1.00 | 0.60 | 0.58 | 0.60 | 0.56 | 0.57 |\n",
       "| survived | 0.37 | 0.75 | 0.60 | 1.00 | 0.81 | 0.74 | 0.71 | 0.73 |\n",
       "| sex | 0.36 | 0.74 | 0.58 | 0.81 | 1.00 | 0.72 | 0.71 | 0.73 |\n",
       "| embarked | 0.39 | 0.74 | 0.60 | 0.74 | 0.72 | 1.00 | 0.69 | 0.71 |\n",
       "| sibsp | 0.37 | 0.72 | 0.56 | 0.71 | 0.71 | 0.69 | 1.00 | 0.73 |\n",
       "| parch | 0.37 | 0.74 | 0.57 | 0.73 | 0.73 | 0.71 | 0.73 | 1.00 |\n",
       "\n"
      ],
      "text/plain": [
       "         fare age  pclass survived sex  embarked sibsp parch\n",
       "fare     1.00 0.38 0.40   0.37     0.36 0.39     0.37  0.37 \n",
       "age      0.38 1.00 0.62   0.75     0.74 0.74     0.72  0.74 \n",
       "pclass   0.40 0.62 1.00   0.60     0.58 0.60     0.56  0.57 \n",
       "survived 0.37 0.75 0.60   1.00     0.81 0.74     0.71  0.73 \n",
       "sex      0.36 0.74 0.58   0.81     1.00 0.72     0.71  0.73 \n",
       "embarked 0.39 0.74 0.60   0.74     0.72 1.00     0.69  0.71 \n",
       "sibsp    0.37 0.72 0.56   0.71     0.71 0.69     1.00  0.73 \n",
       "parch    0.37 0.74 0.57   0.73     0.73 0.71     0.73  1.00 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(computeSimilarityVar(res), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ZBl2WQyvfTSS7feequHh4enp+eYMWO+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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "heatmapClass(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A matrix: 13 × 13 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>Class 1</th><th scope=col>Class 2</th><th scope=col>Class 3</th><th scope=col>Class 4</th><th scope=col>Class 5</th><th scope=col>Class 6</th><th scope=col>Class 7</th><th scope=col>Class 8</th><th scope=col>Class 9</th><th scope=col>Class 10</th><th scope=col>Class 11</th><th scope=col>Class 12</th><th scope=col>Class 13</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Class 1</th><td>1.00</td><td>0.55</td><td>0.49</td><td>0.55</td><td>0.53</td><td>0.53</td><td>0.45</td><td>0.56</td><td>0.55</td><td>0.60</td><td>0.56</td><td>0.53</td><td>0.57</td></tr>\n",
       "\t<tr><th scope=row>Class 2</th><td>0.55</td><td>1.00</td><td>0.61</td><td>0.68</td><td>0.65</td><td>0.66</td><td>0.55</td><td>0.70</td><td>0.69</td><td>0.77</td><td>0.71</td><td>0.67</td><td>0.73</td></tr>\n",
       "\t<tr><th scope=row>Class 3</th><td>0.49</td><td>0.61</td><td>1.00</td><td>0.60</td><td>0.58</td><td>0.59</td><td>0.53</td><td>0.61</td><td>0.61</td><td>0.67</td><td>0.63</td><td>0.59</td><td>0.64</td></tr>\n",
       "\t<tr><th scope=row>Class 4</th><td>0.55</td><td>0.68</td><td>0.60</td><td>1.00</td><td>0.64</td><td>0.65</td><td>0.54</td><td>0.68</td><td>0.68</td><td>0.76</td><td>0.70</td><td>0.66</td><td>0.72</td></tr>\n",
       "\t<tr><th scope=row>Class 5</th><td>0.53</td><td>0.65</td><td>0.58</td><td>0.64</td><td>1.00</td><td>0.62</td><td>0.52</td><td>0.65</td><td>0.65</td><td>0.72</td><td>0.67</td><td>0.63</td><td>0.68</td></tr>\n",
       "\t<tr><th scope=row>Class 6</th><td>0.53</td><td>0.66</td><td>0.59</td><td>0.65</td><td>0.62</td><td>1.00</td><td>0.53</td><td>0.66</td><td>0.67</td><td>0.73</td><td>0.68</td><td>0.64</td><td>0.69</td></tr>\n",
       "\t<tr><th scope=row>Class 7</th><td>0.45</td><td>0.55</td><td>0.53</td><td>0.54</td><td>0.52</td><td>0.53</td><td>1.00</td><td>0.55</td><td>0.55</td><td>0.60</td><td>0.57</td><td>0.53</td><td>0.58</td></tr>\n",
       "\t<tr><th scope=row>Class 8</th><td>0.56</td><td>0.70</td><td>0.61</td><td>0.68</td><td>0.65</td><td>0.66</td><td>0.55</td><td>1.00</td><td>0.69</td><td>0.77</td><td>0.73</td><td>0.67</td><td>0.74</td></tr>\n",
       "\t<tr><th scope=row>Class 9</th><td>0.55</td><td>0.69</td><td>0.61</td><td>0.68</td><td>0.65</td><td>0.67</td><td>0.55</td><td>0.69</td><td>1.00</td><td>0.77</td><td>0.72</td><td>0.67</td><td>0.73</td></tr>\n",
       "\t<tr><th scope=row>Class 10</th><td>0.60</td><td>0.77</td><td>0.67</td><td>0.76</td><td>0.72</td><td>0.73</td><td>0.60</td><td>0.77</td><td>0.77</td><td>1.00</td><td>0.80</td><td>0.74</td><td>0.83</td></tr>\n",
       "\t<tr><th scope=row>Class 11</th><td>0.56</td><td>0.71</td><td>0.63</td><td>0.70</td><td>0.67</td><td>0.68</td><td>0.57</td><td>0.73</td><td>0.72</td><td>0.80</td><td>1.00</td><td>0.68</td><td>0.75</td></tr>\n",
       "\t<tr><th scope=row>Class 12</th><td>0.53</td><td>0.67</td><td>0.59</td><td>0.66</td><td>0.63</td><td>0.64</td><td>0.53</td><td>0.67</td><td>0.67</td><td>0.74</td><td>0.68</td><td>1.00</td><td>0.70</td></tr>\n",
       "\t<tr><th scope=row>Class 13</th><td>0.57</td><td>0.73</td><td>0.64</td><td>0.72</td><td>0.68</td><td>0.69</td><td>0.58</td><td>0.74</td><td>0.73</td><td>0.83</td><td>0.75</td><td>0.70</td><td>1.00</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 13 × 13 of type dbl\n",
       "\\begin{tabular}{r|lllllllllllll}\n",
       "  & Class 1 & Class 2 & Class 3 & Class 4 & Class 5 & Class 6 & Class 7 & Class 8 & Class 9 & Class 10 & Class 11 & Class 12 & Class 13\\\\\n",
       "\\hline\n",
       "\tClass 1 & 1.00 & 0.55 & 0.49 & 0.55 & 0.53 & 0.53 & 0.45 & 0.56 & 0.55 & 0.60 & 0.56 & 0.53 & 0.57\\\\\n",
       "\tClass 2 & 0.55 & 1.00 & 0.61 & 0.68 & 0.65 & 0.66 & 0.55 & 0.70 & 0.69 & 0.77 & 0.71 & 0.67 & 0.73\\\\\n",
       "\tClass 3 & 0.49 & 0.61 & 1.00 & 0.60 & 0.58 & 0.59 & 0.53 & 0.61 & 0.61 & 0.67 & 0.63 & 0.59 & 0.64\\\\\n",
       "\tClass 4 & 0.55 & 0.68 & 0.60 & 1.00 & 0.64 & 0.65 & 0.54 & 0.68 & 0.68 & 0.76 & 0.70 & 0.66 & 0.72\\\\\n",
       "\tClass 5 & 0.53 & 0.65 & 0.58 & 0.64 & 1.00 & 0.62 & 0.52 & 0.65 & 0.65 & 0.72 & 0.67 & 0.63 & 0.68\\\\\n",
       "\tClass 6 & 0.53 & 0.66 & 0.59 & 0.65 & 0.62 & 1.00 & 0.53 & 0.66 & 0.67 & 0.73 & 0.68 & 0.64 & 0.69\\\\\n",
       "\tClass 7 & 0.45 & 0.55 & 0.53 & 0.54 & 0.52 & 0.53 & 1.00 & 0.55 & 0.55 & 0.60 & 0.57 & 0.53 & 0.58\\\\\n",
       "\tClass 8 & 0.56 & 0.70 & 0.61 & 0.68 & 0.65 & 0.66 & 0.55 & 1.00 & 0.69 & 0.77 & 0.73 & 0.67 & 0.74\\\\\n",
       "\tClass 9 & 0.55 & 0.69 & 0.61 & 0.68 & 0.65 & 0.67 & 0.55 & 0.69 & 1.00 & 0.77 & 0.72 & 0.67 & 0.73\\\\\n",
       "\tClass 10 & 0.60 & 0.77 & 0.67 & 0.76 & 0.72 & 0.73 & 0.60 & 0.77 & 0.77 & 1.00 & 0.80 & 0.74 & 0.83\\\\\n",
       "\tClass 11 & 0.56 & 0.71 & 0.63 & 0.70 & 0.67 & 0.68 & 0.57 & 0.73 & 0.72 & 0.80 & 1.00 & 0.68 & 0.75\\\\\n",
       "\tClass 12 & 0.53 & 0.67 & 0.59 & 0.66 & 0.63 & 0.64 & 0.53 & 0.67 & 0.67 & 0.74 & 0.68 & 1.00 & 0.70\\\\\n",
       "\tClass 13 & 0.57 & 0.73 & 0.64 & 0.72 & 0.68 & 0.69 & 0.58 & 0.74 & 0.73 & 0.83 & 0.75 & 0.70 & 1.00\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 13 × 13 of type dbl\n",
       "\n",
       "| <!--/--> | Class 1 | Class 2 | Class 3 | Class 4 | Class 5 | Class 6 | Class 7 | Class 8 | Class 9 | Class 10 | Class 11 | Class 12 | Class 13 |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| Class 1 | 1.00 | 0.55 | 0.49 | 0.55 | 0.53 | 0.53 | 0.45 | 0.56 | 0.55 | 0.60 | 0.56 | 0.53 | 0.57 |\n",
       "| Class 2 | 0.55 | 1.00 | 0.61 | 0.68 | 0.65 | 0.66 | 0.55 | 0.70 | 0.69 | 0.77 | 0.71 | 0.67 | 0.73 |\n",
       "| Class 3 | 0.49 | 0.61 | 1.00 | 0.60 | 0.58 | 0.59 | 0.53 | 0.61 | 0.61 | 0.67 | 0.63 | 0.59 | 0.64 |\n",
       "| Class 4 | 0.55 | 0.68 | 0.60 | 1.00 | 0.64 | 0.65 | 0.54 | 0.68 | 0.68 | 0.76 | 0.70 | 0.66 | 0.72 |\n",
       "| Class 5 | 0.53 | 0.65 | 0.58 | 0.64 | 1.00 | 0.62 | 0.52 | 0.65 | 0.65 | 0.72 | 0.67 | 0.63 | 0.68 |\n",
       "| Class 6 | 0.53 | 0.66 | 0.59 | 0.65 | 0.62 | 1.00 | 0.53 | 0.66 | 0.67 | 0.73 | 0.68 | 0.64 | 0.69 |\n",
       "| Class 7 | 0.45 | 0.55 | 0.53 | 0.54 | 0.52 | 0.53 | 1.00 | 0.55 | 0.55 | 0.60 | 0.57 | 0.53 | 0.58 |\n",
       "| Class 8 | 0.56 | 0.70 | 0.61 | 0.68 | 0.65 | 0.66 | 0.55 | 1.00 | 0.69 | 0.77 | 0.73 | 0.67 | 0.74 |\n",
       "| Class 9 | 0.55 | 0.69 | 0.61 | 0.68 | 0.65 | 0.67 | 0.55 | 0.69 | 1.00 | 0.77 | 0.72 | 0.67 | 0.73 |\n",
       "| Class 10 | 0.60 | 0.77 | 0.67 | 0.76 | 0.72 | 0.73 | 0.60 | 0.77 | 0.77 | 1.00 | 0.80 | 0.74 | 0.83 |\n",
       "| Class 11 | 0.56 | 0.71 | 0.63 | 0.70 | 0.67 | 0.68 | 0.57 | 0.73 | 0.72 | 0.80 | 1.00 | 0.68 | 0.75 |\n",
       "| Class 12 | 0.53 | 0.67 | 0.59 | 0.66 | 0.63 | 0.64 | 0.53 | 0.67 | 0.67 | 0.74 | 0.68 | 1.00 | 0.70 |\n",
       "| Class 13 | 0.57 | 0.73 | 0.64 | 0.72 | 0.68 | 0.69 | 0.58 | 0.74 | 0.73 | 0.83 | 0.75 | 0.70 | 1.00 |\n",
       "\n"
      ],
      "text/plain": [
       "         Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Class 7 Class 8\n",
       "Class 1  1.00    0.55    0.49    0.55    0.53    0.53    0.45    0.56   \n",
       "Class 2  0.55    1.00    0.61    0.68    0.65    0.66    0.55    0.70   \n",
       "Class 3  0.49    0.61    1.00    0.60    0.58    0.59    0.53    0.61   \n",
       "Class 4  0.55    0.68    0.60    1.00    0.64    0.65    0.54    0.68   \n",
       "Class 5  0.53    0.65    0.58    0.64    1.00    0.62    0.52    0.65   \n",
       "Class 6  0.53    0.66    0.59    0.65    0.62    1.00    0.53    0.66   \n",
       "Class 7  0.45    0.55    0.53    0.54    0.52    0.53    1.00    0.55   \n",
       "Class 8  0.56    0.70    0.61    0.68    0.65    0.66    0.55    1.00   \n",
       "Class 9  0.55    0.69    0.61    0.68    0.65    0.67    0.55    0.69   \n",
       "Class 10 0.60    0.77    0.67    0.76    0.72    0.73    0.60    0.77   \n",
       "Class 11 0.56    0.71    0.63    0.70    0.67    0.68    0.57    0.73   \n",
       "Class 12 0.53    0.67    0.59    0.66    0.63    0.64    0.53    0.67   \n",
       "Class 13 0.57    0.73    0.64    0.72    0.68    0.69    0.58    0.74   \n",
       "         Class 9 Class 10 Class 11 Class 12 Class 13\n",
       "Class 1  0.55    0.60     0.56     0.53     0.57    \n",
       "Class 2  0.69    0.77     0.71     0.67     0.73    \n",
       "Class 3  0.61    0.67     0.63     0.59     0.64    \n",
       "Class 4  0.68    0.76     0.70     0.66     0.72    \n",
       "Class 5  0.65    0.72     0.67     0.63     0.68    \n",
       "Class 6  0.67    0.73     0.68     0.64     0.69    \n",
       "Class 7  0.55    0.60     0.57     0.53     0.58    \n",
       "Class 8  0.69    0.77     0.73     0.67     0.74    \n",
       "Class 9  1.00    0.77     0.72     0.67     0.73    \n",
       "Class 10 0.77    1.00     0.80     0.74     0.83    \n",
       "Class 11 0.72    0.80     1.00     0.68     0.75    \n",
       "Class 12 0.67    0.74     0.68     1.00     0.70    \n",
       "Class 13 0.73    0.83     0.75     0.70     1.00    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(computeSimilarityClass(res), 2)"
   ]
  }
 ],
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