diff --git a/.ipynb_checkpoints/test-checkpoint.ipynb b/.ipynb_checkpoints/test-checkpoint.ipynb
deleted file mode 100644
index e92fe3c..0000000
--- a/.ipynb_checkpoints/test-checkpoint.ipynb
+++ /dev/null
@@ -1,635 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "afc3548e-91c2-4443-bd96-457a57a202cc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from mdlp import MDLP\n",
-    "import pandas as pd\n",
-    "from benchmark import Datasets\n",
-    "from bayesclass import TAN"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "8ff3f4d6-e681-4252-ac4d-dc5bd14dcede",
-   "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>RI</th>\n",
-       "      <th>Na</th>\n",
-       "      <th>Mg</th>\n",
-       "      <th>Al</th>\n",
-       "      <th>Si</th>\n",
-       "      <th>'K'</th>\n",
-       "      <th>Ca</th>\n",
-       "      <th>Ba</th>\n",
-       "      <th>Fe</th>\n",
-       "      <th>Type</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1.51793</td>\n",
-       "      <td>12.79</td>\n",
-       "      <td>3.50</td>\n",
-       "      <td>1.12</td>\n",
-       "      <td>73.03</td>\n",
-       "      <td>0.64</td>\n",
-       "      <td>8.77</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1.51643</td>\n",
-       "      <td>12.16</td>\n",
-       "      <td>3.52</td>\n",
-       "      <td>1.35</td>\n",
-       "      <td>72.89</td>\n",
-       "      <td>0.57</td>\n",
-       "      <td>8.53</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1.51793</td>\n",
-       "      <td>13.21</td>\n",
-       "      <td>3.48</td>\n",
-       "      <td>1.41</td>\n",
-       "      <td>72.64</td>\n",
-       "      <td>0.59</td>\n",
-       "      <td>8.43</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1.51299</td>\n",
-       "      <td>14.40</td>\n",
-       "      <td>1.74</td>\n",
-       "      <td>1.54</td>\n",
-       "      <td>74.55</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>7.59</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1.53393</td>\n",
-       "      <td>12.30</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>1.00</td>\n",
-       "      <td>70.16</td>\n",
-       "      <td>0.12</td>\n",
-       "      <td>16.19</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.24</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "        RI     Na    Mg    Al     Si   'K'     Ca   Ba    Fe  Type\n",
-       "0  1.51793  12.79  3.50  1.12  73.03  0.64   8.77  0.0  0.00     0\n",
-       "1  1.51643  12.16  3.52  1.35  72.89  0.57   8.53  0.0  0.00     1\n",
-       "2  1.51793  13.21  3.48  1.41  72.64  0.59   8.43  0.0  0.00     0\n",
-       "3  1.51299  14.40  1.74  1.54  74.55  0.00   7.59  0.0  0.00     2\n",
-       "4  1.53393  12.30  0.00  1.00  70.16  0.12  16.19  0.0  0.24     3"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Get data as a dataset\n",
-    "dt = Datasets()\n",
-    "data = dt.load(\"glass\", dataframe=True)\n",
-    "features = dt.dataset.features\n",
-    "class_name = dt.dataset.class_name\n",
-    "factorization, class_factors = pd.factorize(data[class_name])\n",
-    "data[class_name] = factorization\n",
-    "data.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "7c9e1eae-6a66-4930-a125-f9f3def45574",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\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>RI</th>\n",
-       "      <th>Na</th>\n",
-       "      <th>Mg</th>\n",
-       "      <th>Al</th>\n",
-       "      <th>Si</th>\n",
-       "      <th>'K'</th>\n",
-       "      <th>Ca</th>\n",
-       "      <th>Ba</th>\n",
-       "      <th>Fe</th>\n",
-       "      <th>Type</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>30.0</td>\n",
-       "      <td>14.0</td>\n",
-       "      <td>16.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>38.0</td>\n",
-       "      <td>32.0</td>\n",
-       "      <td>14.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>17.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>21.0</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>30.0</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>51.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>47.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>62.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>13.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>30.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>209</th>\n",
-       "      <td>13.0</td>\n",
-       "      <td>33.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>19.0</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>27.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>210</th>\n",
-       "      <td>11.0</td>\n",
-       "      <td>19.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>29.0</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>33.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>211</th>\n",
-       "      <td>14.0</td>\n",
-       "      <td>41.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>20.0</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>14.0</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>212</th>\n",
-       "      <td>20.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>42.0</td>\n",
-       "      <td>33.0</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>213</th>\n",
-       "      <td>43.0</td>\n",
-       "      <td>46.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>23.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>2</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>214 rows × 10 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       RI    Na    Mg    Al    Si   'K'    Ca   Ba   Fe  Type\n",
-       "0    30.0  14.0  16.0  18.0  38.0  32.0  14.0  0.0  0.0     0\n",
-       "1    17.0   3.0  18.0  21.0  34.0  24.0  10.0  0.0  0.0     1\n",
-       "2    30.0  24.0  15.0  22.0  22.0  27.0   6.0  0.0  0.0     0\n",
-       "3     3.0  51.0   6.0  23.0  47.0   0.0   3.0  0.0  0.0     2\n",
-       "4    62.0   4.0   0.0  13.0   0.0   8.0  30.0  0.0  5.0     3\n",
-       "..    ...   ...   ...   ...   ...   ...   ...  ...  ...   ...\n",
-       "209  13.0  33.0  11.0  19.0  23.0  27.0   4.0  0.0  0.0     1\n",
-       "210  11.0  19.0  18.0  29.0  23.0  33.0   3.0  0.0  0.0     3\n",
-       "211  14.0  41.0  18.0  20.0  34.0  14.0   3.0  0.0  5.0     3\n",
-       "212  20.0   8.0   8.0  23.0  42.0  33.0  11.0  0.0  0.0     3\n",
-       "213  43.0  46.0   6.0  23.0  23.0   0.0  15.0  0.0  0.0     2\n",
-       "\n",
-       "[214 rows x 10 columns]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Fayyad Irani\n",
-    "discretiz = MDLP()\n",
-    "Xdisc = discretiz.fit_transform(\n",
-    "    data[features].to_numpy(), data[class_name].to_numpy()\n",
-    ")\n",
-    "features_discretized = pd.DataFrame(Xdisc, columns=features)\n",
-    "dataset_discretized = features_discretized.copy()\n",
-    "dataset_discretized[class_name] = data[class_name]\n",
-    "X = dataset_discretized[features]\n",
-    "y = dataset_discretized[class_name]\n",
-    "dataset_discretized"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "2840a103-99fb-466f-ae75-45e11c1b9c5a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.model_selection import cross_validate, StratifiedKFold, KFold, cross_val_score\n",
-    "import numpy as np\n",
-    "n_folds = 5\n",
-    "score_name = \"accuracy\"\n",
-    "random_state=17\n",
-    "def validate_classifier(model, X, y, stratified, fit_params):\n",
-    "    stratified_class = StratifiedKFold if stratified else KFold\n",
-    "    kfold = stratified_class(shuffle=True, random_state=random_state, n_splits=n_folds)\n",
-    "    #return cross_validate(model, X, y, cv=kfold, return_estimator=True, scoring=score_name)\n",
-    "    return cross_val_score(model, X, y, fit_params=fit_params)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "6a1aad95-370f-4854-ae9a-32205aff5d39",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b620372c05294afc853885da0848e389",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
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-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ad33ee9f224d4abfa9a23338f07b32f2",
-       "version_major": 2,
-       "version_minor": 0
-      },
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-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fa05948fc73d43da8a3f01adc71c5e53",
-       "version_major": 2,
-       "version_minor": 0
-      },
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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1b67f117ceed43818c98342221b11184",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "  0%|          | 0/43 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2399fb4327a242f0bd1c3e64b84382a6",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "  0%|          | 0/42 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n",
-      "/Users/rmontanana/Code/pgmpy/pgmpy/factors/discrete/DiscreteFactor.py:541: UserWarning: Found unknown state name. Trying to switch to using all state names as state numbers\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "ename": "IndexError",
-     "evalue": "only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn [19], line 9\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m head \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m4\u001b[39m):\n\u001b[1;32m      7\u001b[0m     \u001b[38;5;66;03m#model.fit(X, y, head=head, features=features, class_name=class_name)\u001b[39;00m\n\u001b[1;32m      8\u001b[0m     score \u001b[38;5;241m=\u001b[39m validate_classifier(model, X, y, stratified\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, fit_params\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mdict\u001b[39m(head\u001b[38;5;241m=\u001b[39mhead, features\u001b[38;5;241m=\u001b[39mfeatures, class_name\u001b[38;5;241m=\u001b[39mclass_name))\n\u001b[0;32m----> 9\u001b[0m     model\u001b[38;5;241m.\u001b[39mplot(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msimple_init=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00msimple_init\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m head=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mhead\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m  score=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mmean(score[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtest_score\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
-      "\u001b[0;31mIndexError\u001b[0m: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices"
-     ]
-    }
-   ],
-   "source": [
-    "import warnings\n",
-    "from stree import Stree\n",
-    "warnings.filterwarnings('ignore')\n",
-    "for simple_init in [False, True]:\n",
-    "    model = TAN(simple_init=simple_init)\n",
-    "    for head in range(4):\n",
-    "        #model.fit(X, y, head=head, features=features, class_name=class_name)\n",
-    "        score = validate_classifier(model, X, y, stratified=False, fit_params=dict(head=head, features=features, class_name=class_name))\n",
-    "        #model.plot(f\"simple_init={simple_init} head={head}  score={np.mean(score['test_score'])}\")\n",
-    "        model.plot(f\"simple_init={simple_init} head={head}  score={np.mean(score)}\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c389ff1e-76d9-4c5b-9860-ea6d4752fac7",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9c58629f-000b-4d8c-8896-efd032f1090c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "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": "3.10.8"
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-  "vscode": {
-   "interpreter": {
-    "hash": "a5f800306069c11c1b9a793f47dfeb8c7d63d06a771fda00cf3476e3d4088a52"
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- "nbformat": 4,
- "nbformat_minor": 5
-}