diff --git a/info.ipynb b/info.ipynb
index 9f4fb4e3..833e2bee 100644
--- a/info.ipynb
+++ b/info.ipynb
@@ -7,480 +7,15 @@
    "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>age</th>\n",
-       "      <th>workclass</th>\n",
-       "      <th>fnlwgt</th>\n",
-       "      <th>education</th>\n",
-       "      <th>education.num</th>\n",
-       "      <th>marital.status</th>\n",
-       "      <th>occupation</th>\n",
-       "      <th>relationship</th>\n",
-       "      <th>race</th>\n",
-       "      <th>sex</th>\n",
-       "      <th>capital.gain</th>\n",
-       "      <th>capital.loss</th>\n",
-       "      <th>hours.per.week</th>\n",
-       "      <th>native.country</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>32541</th>\n",
-       "      <td>71</td>\n",
-       "      <td>?</td>\n",
-       "      <td>287372</td>\n",
-       "      <td>Doctorate</td>\n",
-       "      <td>16</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>?</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>10</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32542</th>\n",
-       "      <td>45</td>\n",
-       "      <td>State-gov</td>\n",
-       "      <td>252208</td>\n",
-       "      <td>HS-grad</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Separated</td>\n",
-       "      <td>Adm-clerical</td>\n",
-       "      <td>Own-child</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32543</th>\n",
-       "      <td>41</td>\n",
-       "      <td>?</td>\n",
-       "      <td>202822</td>\n",
-       "      <td>HS-grad</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Separated</td>\n",
-       "      <td>?</td>\n",
-       "      <td>Not-in-family</td>\n",
-       "      <td>Black</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>32</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32544</th>\n",
-       "      <td>72</td>\n",
-       "      <td>?</td>\n",
-       "      <td>129912</td>\n",
-       "      <td>HS-grad</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>?</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32545</th>\n",
-       "      <td>45</td>\n",
-       "      <td>Local-gov</td>\n",
-       "      <td>119199</td>\n",
-       "      <td>Assoc-acdm</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Divorced</td>\n",
-       "      <td>Prof-specialty</td>\n",
-       "      <td>Unmarried</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>48</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32546</th>\n",
-       "      <td>31</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>199655</td>\n",
-       "      <td>Masters</td>\n",
-       "      <td>14</td>\n",
-       "      <td>Divorced</td>\n",
-       "      <td>Other-service</td>\n",
-       "      <td>Not-in-family</td>\n",
-       "      <td>Other</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>30</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32547</th>\n",
-       "      <td>39</td>\n",
-       "      <td>Local-gov</td>\n",
-       "      <td>111499</td>\n",
-       "      <td>Assoc-acdm</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Adm-clerical</td>\n",
-       "      <td>Wife</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>20</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32548</th>\n",
-       "      <td>37</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>198216</td>\n",
-       "      <td>Assoc-acdm</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Divorced</td>\n",
-       "      <td>Tech-support</td>\n",
-       "      <td>Not-in-family</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32549</th>\n",
-       "      <td>43</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>260761</td>\n",
-       "      <td>HS-grad</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Machine-op-inspct</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>Mexico</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32550</th>\n",
-       "      <td>43</td>\n",
-       "      <td>State-gov</td>\n",
-       "      <td>255835</td>\n",
-       "      <td>Some-college</td>\n",
-       "      <td>10</td>\n",
-       "      <td>Divorced</td>\n",
-       "      <td>Adm-clerical</td>\n",
-       "      <td>Other-relative</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32551</th>\n",
-       "      <td>43</td>\n",
-       "      <td>Self-emp-not-inc</td>\n",
-       "      <td>27242</td>\n",
-       "      <td>Some-college</td>\n",
-       "      <td>10</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Craft-repair</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>50</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32552</th>\n",
-       "      <td>32</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>34066</td>\n",
-       "      <td>10th</td>\n",
-       "      <td>6</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Handlers-cleaners</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>Amer-Indian-Eskimo</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32553</th>\n",
-       "      <td>43</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>84661</td>\n",
-       "      <td>Assoc-voc</td>\n",
-       "      <td>11</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Sales</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>45</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32554</th>\n",
-       "      <td>32</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>116138</td>\n",
-       "      <td>Masters</td>\n",
-       "      <td>14</td>\n",
-       "      <td>Never-married</td>\n",
-       "      <td>Tech-support</td>\n",
-       "      <td>Not-in-family</td>\n",
-       "      <td>Asian-Pac-Islander</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11</td>\n",
-       "      <td>Taiwan</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32555</th>\n",
-       "      <td>53</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>321865</td>\n",
-       "      <td>Masters</td>\n",
-       "      <td>14</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Exec-managerial</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32556</th>\n",
-       "      <td>22</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>310152</td>\n",
-       "      <td>Some-college</td>\n",
-       "      <td>10</td>\n",
-       "      <td>Never-married</td>\n",
-       "      <td>Protective-serv</td>\n",
-       "      <td>Not-in-family</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32557</th>\n",
-       "      <td>27</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>257302</td>\n",
-       "      <td>Assoc-acdm</td>\n",
-       "      <td>12</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Tech-support</td>\n",
-       "      <td>Wife</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>38</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32558</th>\n",
-       "      <td>40</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>154374</td>\n",
-       "      <td>HS-grad</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Married-civ-spouse</td>\n",
-       "      <td>Machine-op-inspct</td>\n",
-       "      <td>Husband</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32559</th>\n",
-       "      <td>58</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>151910</td>\n",
-       "      <td>HS-grad</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Widowed</td>\n",
-       "      <td>Adm-clerical</td>\n",
-       "      <td>Unmarried</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>40</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32560</th>\n",
-       "      <td>22</td>\n",
-       "      <td>Private</td>\n",
-       "      <td>201490</td>\n",
-       "      <td>HS-grad</td>\n",
-       "      <td>9</td>\n",
-       "      <td>Never-married</td>\n",
-       "      <td>Adm-clerical</td>\n",
-       "      <td>Own-child</td>\n",
-       "      <td>White</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>20</td>\n",
-       "      <td>United-States</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       age         workclass  fnlwgt     education  education.num  \\\n",
-       "32541   71                 ?  287372     Doctorate             16   \n",
-       "32542   45         State-gov  252208       HS-grad              9   \n",
-       "32543   41                 ?  202822       HS-grad              9   \n",
-       "32544   72                 ?  129912       HS-grad              9   \n",
-       "32545   45         Local-gov  119199    Assoc-acdm             12   \n",
-       "32546   31           Private  199655       Masters             14   \n",
-       "32547   39         Local-gov  111499    Assoc-acdm             12   \n",
-       "32548   37           Private  198216    Assoc-acdm             12   \n",
-       "32549   43           Private  260761       HS-grad              9   \n",
-       "32550   43         State-gov  255835  Some-college             10   \n",
-       "32551   43  Self-emp-not-inc   27242  Some-college             10   \n",
-       "32552   32           Private   34066          10th              6   \n",
-       "32553   43           Private   84661     Assoc-voc             11   \n",
-       "32554   32           Private  116138       Masters             14   \n",
-       "32555   53           Private  321865       Masters             14   \n",
-       "32556   22           Private  310152  Some-college             10   \n",
-       "32557   27           Private  257302    Assoc-acdm             12   \n",
-       "32558   40           Private  154374       HS-grad              9   \n",
-       "32559   58           Private  151910       HS-grad              9   \n",
-       "32560   22           Private  201490       HS-grad              9   \n",
-       "\n",
-       "           marital.status         occupation    relationship  \\\n",
-       "32541  Married-civ-spouse                  ?         Husband   \n",
-       "32542           Separated       Adm-clerical       Own-child   \n",
-       "32543           Separated                  ?   Not-in-family   \n",
-       "32544  Married-civ-spouse                  ?         Husband   \n",
-       "32545            Divorced     Prof-specialty       Unmarried   \n",
-       "32546            Divorced      Other-service   Not-in-family   \n",
-       "32547  Married-civ-spouse       Adm-clerical            Wife   \n",
-       "32548            Divorced       Tech-support   Not-in-family   \n",
-       "32549  Married-civ-spouse  Machine-op-inspct         Husband   \n",
-       "32550            Divorced       Adm-clerical  Other-relative   \n",
-       "32551  Married-civ-spouse       Craft-repair         Husband   \n",
-       "32552  Married-civ-spouse  Handlers-cleaners         Husband   \n",
-       "32553  Married-civ-spouse              Sales         Husband   \n",
-       "32554       Never-married       Tech-support   Not-in-family   \n",
-       "32555  Married-civ-spouse    Exec-managerial         Husband   \n",
-       "32556       Never-married    Protective-serv   Not-in-family   \n",
-       "32557  Married-civ-spouse       Tech-support            Wife   \n",
-       "32558  Married-civ-spouse  Machine-op-inspct         Husband   \n",
-       "32559             Widowed       Adm-clerical       Unmarried   \n",
-       "32560       Never-married       Adm-clerical       Own-child   \n",
-       "\n",
-       "                     race     sex  capital.gain  capital.loss  hours.per.week  \\\n",
-       "32541               White    Male             0             0              10   \n",
-       "32542               White  Female             0             0              40   \n",
-       "32543               Black  Female             0             0              32   \n",
-       "32544               White    Male             0             0              25   \n",
-       "32545               White  Female             0             0              48   \n",
-       "32546               Other  Female             0             0              30   \n",
-       "32547               White  Female             0             0              20   \n",
-       "32548               White  Female             0             0              40   \n",
-       "32549               White    Male             0             0              40   \n",
-       "32550               White  Female             0             0              40   \n",
-       "32551               White    Male             0             0              50   \n",
-       "32552  Amer-Indian-Eskimo    Male             0             0              40   \n",
-       "32553               White    Male             0             0              45   \n",
-       "32554  Asian-Pac-Islander    Male             0             0              11   \n",
-       "32555               White    Male             0             0              40   \n",
-       "32556               White    Male             0             0              40   \n",
-       "32557               White  Female             0             0              38   \n",
-       "32558               White    Male             0             0              40   \n",
-       "32559               White  Female             0             0              40   \n",
-       "32560               White    Male             0             0              20   \n",
-       "\n",
-       "      native.country  \n",
-       "32541  United-States  \n",
-       "32542  United-States  \n",
-       "32543  United-States  \n",
-       "32544  United-States  \n",
-       "32545  United-States  \n",
-       "32546  United-States  \n",
-       "32547  United-States  \n",
-       "32548  United-States  \n",
-       "32549         Mexico  \n",
-       "32550  United-States  \n",
-       "32551  United-States  \n",
-       "32552  United-States  \n",
-       "32553  United-States  \n",
-       "32554         Taiwan  \n",
-       "32555  United-States  \n",
-       "32556  United-States  \n",
-       "32557  United-States  \n",
-       "32558  United-States  \n",
-       "32559  United-States  \n",
-       "32560  United-States  "
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "TypeError",
+     "evalue": "'numpy.ndarray' object is not callable",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mTypeError\u001b[39m                                 Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[25]\u001b[39m\u001b[32m, line 20\u001b[39m\n\u001b[32m     18\u001b[39m X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=\u001b[32m0.2\u001b[39m, random_state=\u001b[32m42\u001b[39m)\n\u001b[32m     19\u001b[39m X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=\u001b[32m0.2\u001b[39m, random_state=\u001b[32m42\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m20\u001b[39m X_train = \u001b[43mX_train\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     23\u001b[39m n_features = \u001b[32m10\u001b[39m\n\u001b[32m     24\u001b[39m fig=plt.figure( figsize=(\u001b[32m15\u001b[39m, \u001b[32m15\u001b[39m) )\n",
+      "\u001b[31mTypeError\u001b[39m: 'numpy.ndarray' object is not callable"
+     ]
     }
    ],
    "source": [
@@ -489,23 +24,51 @@
     "import matplotlib.pyplot as plt\n",
     "from sklearn.model_selection import train_test_split\n",
     "from sklearn.pipeline import Pipeline\n",
+    "from sklearn.tree import DecisionTreeClassifier, plot_tree\n",
+    "from sklearn.preprocessing import LabelEncoder\n",
     "\n",
+    "df = pd.read_csv('./Datasets/adult.csv', comment = '#')\n",
     "\n",
+    "# First, create a copy of the dataframe to avoid modifying the original\n",
+    "df_encoded = df.copy()\n",
     "\n",
-    "data = pd.read_csv('./Datasets/adult.csv', comment = '#')\n",
+    "# Apply label encoding to categorical columns\n",
+    "label_encoder = LabelEncoder()\n",
+    "categorical_columns = ['workclass', 'marital.status', 'occupation', \n",
+    "                      'relationship', 'race', 'sex', 'income']\n",
     "\n",
-    "# Features\n",
-    "X = data.drop(columns=['income'])\n",
-    "\n",
-    "# Labels\n",
-    "y = data['income']\n",
+    "for column in categorical_columns:\n",
+    "    df_encoded[column] = label_encoder.fit_transform(df_encoded[column])\n",
     "\n",
+    "# Now properly separate features and target\n",
+    "X = df_encoded.drop(columns=['income', 'native.country', 'education'])\n",
+    "y = df_encoded['income']\n",
     "\n",
+    "# Split the data\n",
     "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
     "X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=0.2, random_state=42)\n",
     "\n",
-    "X.tail(20)\n",
-    "\n"
+    "\n",
+    "\n",
+    "n_features = 10\n",
+    "fig=plt.figure( figsize=(15, 15) )\n",
+    "plt_num = 1\n",
+    "for i in range(n_features):\n",
+    "    for j in range(n_features):\n",
+    "        ax = fig.add_subplot(n_features, n_features, plt_num)\n",
+    "        if(i == j):\n",
+    "            ax.hist(X_train[:, i], bins=25, color='gray')\n",
+    "        else:\n",
+    "            ax.scatter(X_train[:, j], X_train[:, i], c=np.array(colors)[y_train], s=30, alpha=0.3)\n",
+    "                \n",
+    "        if(i == n_features-1):\n",
+    "            ax.set_xlabel(f'$x_{{{j}}}$', fontsize=22)\n",
+    "        \n",
+    "        if(j==0):\n",
+    "            ax.set_ylabel(f'$x_{{{i}}}$', fontsize=22)\n",
+    "\n",
+    "        ax.grid(True)\n",
+    "        plt_num +=1\n"
    ]
   }
  ],