1921234
/
DSA_SoSe_24
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
DSA_SoSe_24/DecisionTree.ipynb

672 lines
227 KiB
Plaintext
Raw Permalink Normal View History

added decision tree
2024-06-23 11:31:52 +02:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 7,
"id": "156d7fbe-f7f8-4d58-af3c-26cd55a345c4",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from sklearn.tree import DecisionTreeClassifier, plot_tree"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "aea0c6f2-e2c6-4fb7-8c84-6c5cc529e231",
"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>sex</th>\n",
" <th>cp</th>\n",
" <th>trestbps</th>\n",
" <th>chol</th>\n",
" <th>fbs</th>\n",
" <th>restecg</th>\n",
" <th>thalach</th>\n",
" <th>exang</th>\n",
" <th>oldpeak</th>\n",
" <th>slope</th>\n",
" <th>ca</th>\n",
" <th>thal</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>63</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>145</td>\n",
" <td>233</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>150</td>\n",
" <td>0</td>\n",
" <td>2.3</td>\n",
" <td>3</td>\n",
" <td>0.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>67</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>160</td>\n",
" <td>286</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>108</td>\n",
" <td>1</td>\n",
" <td>1.5</td>\n",
" <td>2</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>67</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>120</td>\n",
" <td>229</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>129</td>\n",
" <td>1</td>\n",
" <td>2.6</td>\n",
" <td>2</td>\n",
" <td>2.0</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>37</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>130</td>\n",
" <td>250</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>187</td>\n",
" <td>0</td>\n",
" <td>3.5</td>\n",
" <td>3</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>41</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>130</td>\n",
" <td>204</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>172</td>\n",
" <td>0</td>\n",
" <td>1.4</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" age sex cp trestbps chol fbs restecg thalach exang oldpeak slope \\\n",
"0 63 1 1 145 233 1 2 150 0 2.3 3 \n",
"1 67 1 4 160 286 0 2 108 1 1.5 2 \n",
"2 67 1 4 120 229 0 2 129 1 2.6 2 \n",
"3 37 1 3 130 250 0 0 187 0 3.5 3 \n",
"4 41 0 2 130 204 0 2 172 0 1.4 1 \n",
"\n",
" ca thal \n",
"0 0.0 6.0 \n",
"1 3.0 3.0 \n",
"2 2.0 7.0 \n",
"3 0.0 3.0 \n",
"4 0.0 3.0 "
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv('./data/dataset_cleaned.csv')\n",
"\n",
"# extract all columns except 'goal' --> X\n",
"X = df.loc[:, df.columns != 'goal']\n",
"# extract only the column 'goal' --> y\n",
"y = df.loc[:, 'goal']\n",
"\n",
"# add new axis to y, new shape: (n, 1)\n",
"y = y.to_numpy()\n",
"y = y.reshape((len(y),1))\n",
"\n",
"# binarize y\n",
"y[y>0] = 1\n",
"\n",
"factor_columns = ['sex', 'cp', 'fbs', 'restecg', 'exang', 'slope', 'thal', 'ca']\n",
"numeric_columns = [column for column in X.columns if column not in factor_columns]\n",
"\n",
"# transform factors into onehot vectors\n",
"# X = pd.get_dummies(X, columns=factor_columns)\n",
"\n",
"# min max scaling of numeric columns\n",
"# scaler = MinMaxScaler()\n",
"# X[numeric_columns] = scaler.fit_transform(X[numeric_columns])\n",
"\n",
"X.head()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "a6acb9e5-1f68-4725-b153-7ea4acb2b2ab",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<style>#sk-container-id-3 {\n",
" /* Definition of color scheme common for light and dark mode */\n",
" --sklearn-color-text: black;\n",
" --sklearn-color-line: gray;\n",
" /* Definition of color scheme for unfitted estimators */\n",
" --sklearn-color-unfitted-level-0: #fff5e6;\n",
" --sklearn-color-unfitted-level-1: #f6e4d2;\n",
" --sklearn-color-unfitted-level-2: #ffe0b3;\n",
" --sklearn-color-unfitted-level-3: chocolate;\n",
" /* Definition of color scheme for fitted estimators */\n",
" --sklearn-color-fitted-level-0: #f0f8ff;\n",
" --sklearn-color-fitted-level-1: #d4ebff;\n",
" --sklearn-color-fitted-level-2: #b3dbfd;\n",
" --sklearn-color-fitted-level-3: cornflowerblue;\n",
"\n",
" /* Specific color for light theme */\n",
" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
" --sklearn-color-icon: #696969;\n",
"\n",
" @media (prefers-color-scheme: dark) {\n",
" /* Redefinition of color scheme for dark theme */\n",
" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
" --sklearn-color-icon: #878787;\n",
" }\n",
"}\n",
"\n",
"#sk-container-id-3 {\n",
" color: var(--sklearn-color-text);\n",
"}\n",
"\n",
"#sk-container-id-3 pre {\n",
" padding: 0;\n",
"}\n",
"\n",
"#sk-container-id-3 input.sk-hidden--visually {\n",
" border: 0;\n",
" clip: rect(1px 1px 1px 1px);\n",
" clip: rect(1px, 1px, 1px, 1px);\n",
" height: 1px;\n",
" margin: -1px;\n",
" overflow: hidden;\n",
" padding: 0;\n",
" position: absolute;\n",
" width: 1px;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-dashed-wrapped {\n",
" border: 1px dashed var(--sklearn-color-line);\n",
" margin: 0 0.4em 0.5em 0.4em;\n",
" box-sizing: border-box;\n",
" padding-bottom: 0.4em;\n",
" background-color: var(--sklearn-color-background);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-container {\n",
" /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
" but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
" so we also need the `!important` here to be able to override the\n",
" default hidden behavior on the sphinx rendered scikit-learn.org.\n",
" See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
" display: inline-block !important;\n",
" position: relative;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-text-repr-fallback {\n",
" display: none;\n",
"}\n",
"\n",
"div.sk-parallel-item,\n",
"div.sk-serial,\n",
"div.sk-item {\n",
" /* draw centered vertical line to link estimators */\n",
" background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
" background-size: 2px 100%;\n",
" background-repeat: no-repeat;\n",
" background-position: center center;\n",
"}\n",
"\n",
"/* Parallel-specific style estimator block */\n",
"\n",
"#sk-container-id-3 div.sk-parallel-item::after {\n",
" content: \"\";\n",
" width: 100%;\n",
" border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
" flex-grow: 1;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-parallel {\n",
" display: flex;\n",
" align-items: stretch;\n",
" justify-content: center;\n",
" background-color: var(--sklearn-color-background);\n",
" position: relative;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-parallel-item {\n",
" display: flex;\n",
" flex-direction: column;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
" align-self: flex-end;\n",
" width: 50%;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
" align-self: flex-start;\n",
" width: 50%;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
" width: 0;\n",
"}\n",
"\n",
"/* Serial-specific style estimator block */\n",
"\n",
"#sk-container-id-3 div.sk-serial {\n",
" display: flex;\n",
" flex-direction: column;\n",
" align-items: center;\n",
" background-color: var(--sklearn-color-background);\n",
" padding-right: 1em;\n",
" padding-left: 1em;\n",
"}\n",
"\n",
"\n",
"/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
"clickable and can be expanded/collapsed.\n",
"- Pipeline and ColumnTransformer use this feature and define the default style\n",
"- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
"*/\n",
"\n",
"/* Pipeline and ColumnTransformer style (default) */\n",
"\n",
"#sk-container-id-3 div.sk-toggleable {\n",
" /* Default theme specific background. It is overwritten whether we have a\n",
" specific estimator or a Pipeline/ColumnTransformer */\n",
" background-color: var(--sklearn-color-background);\n",
"}\n",
"\n",
"/* Toggleable label */\n",
"#sk-container-id-3 label.sk-toggleable__label {\n",
" cursor: pointer;\n",
" display: block;\n",
" width: 100%;\n",
" margin-bottom: 0;\n",
" padding: 0.5em;\n",
" box-sizing: border-box;\n",
" text-align: center;\n",
"}\n",
"\n",
"#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
" /* Arrow on the left of the label */\n",
" content: \"▸\";\n",
" float: left;\n",
" margin-right: 0.25em;\n",
" color: var(--sklearn-color-icon);\n",
"}\n",
"\n",
"#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
" color: var(--sklearn-color-text);\n",
"}\n",
"\n",
"/* Toggleable content - dropdown */\n",
"\n",
"#sk-container-id-3 div.sk-toggleable__content {\n",
" max-height: 0;\n",
" max-width: 0;\n",
" overflow: hidden;\n",
" text-align: left;\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-unfitted-level-0);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
" /* fitted */\n",
" background-color: var(--sklearn-color-fitted-level-0);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-toggleable__content pre {\n",
" margin: 0.2em;\n",
" border-radius: 0.25em;\n",
" color: var(--sklearn-color-text);\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-unfitted-level-0);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-fitted-level-0);\n",
"}\n",
"\n",
"#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
" /* Expand drop-down */\n",
" max-height: 200px;\n",
" max-width: 100%;\n",
" overflow: auto;\n",
"}\n",
"\n",
"#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
" content: \"▾\";\n",
"}\n",
"\n",
"/* Pipeline/ColumnTransformer-specific style */\n",
"\n",
"#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
" color: var(--sklearn-color-text);\n",
" background-color: var(--sklearn-color-unfitted-level-2);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
" background-color: var(--sklearn-color-fitted-level-2);\n",
"}\n",
"\n",
"/* Estimator-specific style */\n",
"\n",
"/* Colorize estimator box */\n",
"#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-unfitted-level-2);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
" /* fitted */\n",
" background-color: var(--sklearn-color-fitted-level-2);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
"#sk-container-id-3 div.sk-label label {\n",
" /* The background is the default theme color */\n",
" color: var(--sklearn-color-text-on-default-background);\n",
"}\n",
"\n",
"/* On hover, darken the color of the background */\n",
"#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
" color: var(--sklearn-color-text);\n",
" background-color: var(--sklearn-color-unfitted-level-2);\n",
"}\n",
"\n",
"/* Label box, darken color on hover, fitted */\n",
"#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
" color: var(--sklearn-color-text);\n",
" background-color: var(--sklearn-color-fitted-level-2);\n",
"}\n",
"\n",
"/* Estimator label */\n",
"\n",
"#sk-container-id-3 div.sk-label label {\n",
" font-family: monospace;\n",
" font-weight: bold;\n",
" display: inline-block;\n",
" line-height: 1.2em;\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-label-container {\n",
" text-align: center;\n",
"}\n",
"\n",
"/* Estimator-specific */\n",
"#sk-container-id-3 div.sk-estimator {\n",
" font-family: monospace;\n",
" border: 1px dotted var(--sklearn-color-border-box);\n",
" border-radius: 0.25em;\n",
" box-sizing: border-box;\n",
" margin-bottom: 0.5em;\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-unfitted-level-0);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-estimator.fitted {\n",
" /* fitted */\n",
" background-color: var(--sklearn-color-fitted-level-0);\n",
"}\n",
"\n",
"/* on hover */\n",
"#sk-container-id-3 div.sk-estimator:hover {\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-unfitted-level-2);\n",
"}\n",
"\n",
"#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
" /* fitted */\n",
" background-color: var(--sklearn-color-fitted-level-2);\n",
"}\n",
"\n",
"/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
"\n",
"/* Common style for \"i\" and \"?\" */\n",
"\n",
".sk-estimator-doc-link,\n",
"a:link.sk-estimator-doc-link,\n",
"a:visited.sk-estimator-doc-link {\n",
" float: right;\n",
" font-size: smaller;\n",
" line-height: 1em;\n",
" font-family: monospace;\n",
" background-color: var(--sklearn-color-background);\n",
" border-radius: 1em;\n",
" height: 1em;\n",
" width: 1em;\n",
" text-decoration: none !important;\n",
" margin-left: 1ex;\n",
" /* unfitted */\n",
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
" color: var(--sklearn-color-unfitted-level-1);\n",
"}\n",
"\n",
".sk-estimator-doc-link.fitted,\n",
"a:link.sk-estimator-doc-link.fitted,\n",
"a:visited.sk-estimator-doc-link.fitted {\n",
" /* fitted */\n",
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
" color: var(--sklearn-color-fitted-level-1);\n",
"}\n",
"\n",
"/* On hover */\n",
"div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
".sk-estimator-doc-link:hover,\n",
"div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
".sk-estimator-doc-link:hover {\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-unfitted-level-3);\n",
" color: var(--sklearn-color-background);\n",
" text-decoration: none;\n",
"}\n",
"\n",
"div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
".sk-estimator-doc-link.fitted:hover,\n",
"div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
".sk-estimator-doc-link.fitted:hover {\n",
" /* fitted */\n",
" background-color: var(--sklearn-color-fitted-level-3);\n",
" color: var(--sklearn-color-background);\n",
" text-decoration: none;\n",
"}\n",
"\n",
"/* Span, style for the box shown on hovering the info icon */\n",
".sk-estimator-doc-link span {\n",
" display: none;\n",
" z-index: 9999;\n",
" position: relative;\n",
" font-weight: normal;\n",
" right: .2ex;\n",
" padding: .5ex;\n",
" margin: .5ex;\n",
" width: min-content;\n",
" min-width: 20ex;\n",
" max-width: 50ex;\n",
" color: var(--sklearn-color-text);\n",
" box-shadow: 2pt 2pt 4pt #999;\n",
" /* unfitted */\n",
" background: var(--sklearn-color-unfitted-level-0);\n",
" border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
"}\n",
"\n",
".sk-estimator-doc-link.fitted span {\n",
" /* fitted */\n",
" background: var(--sklearn-color-fitted-level-0);\n",
" border: var(--sklearn-color-fitted-level-3);\n",
"}\n",
"\n",
".sk-estimator-doc-link:hover span {\n",
" display: block;\n",
"}\n",
"\n",
"/* \"?\"-specific style due to the `<a>` HTML tag */\n",
"\n",
"#sk-container-id-3 a.estimator_doc_link {\n",
" float: right;\n",
" font-size: 1rem;\n",
" line-height: 1em;\n",
" font-family: monospace;\n",
" background-color: var(--sklearn-color-background);\n",
" border-radius: 1rem;\n",
" height: 1rem;\n",
" width: 1rem;\n",
" text-decoration: none;\n",
" /* unfitted */\n",
" color: var(--sklearn-color-unfitted-level-1);\n",
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
"}\n",
"\n",
"#sk-container-id-3 a.estimator_doc_link.fitted {\n",
" /* fitted */\n",
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
" color: var(--sklearn-color-fitted-level-1);\n",
"}\n",
"\n",
"/* On hover */\n",
"#sk-container-id-3 a.estimator_doc_link:hover {\n",
" /* unfitted */\n",
" background-color: var(--sklearn-color-unfitted-level-3);\n",
" color: var(--sklearn-color-background);\n",
" text-decoration: none;\n",
"}\n",
"\n",
"#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
" /* fitted */\n",
" background-color: var(--sklearn-color-fitted-level-3);\n",
"}\n",
"</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=3)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=3)</pre></div> </div></div></div></div>"
],
"text/plain": [
"DecisionTreeClassifier(max_depth=3)"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"model = DecisionTreeClassifier(max_depth=3)\n",
"model.fit(X, y)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "44c1e072-414a-413e-a6fc-c1062cda28f3",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 2000x1000 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.figure(figsize=(20,10))\n",
"ax=plot_tree(model, \n",
" feature_names=X.columns,\n",
" class_names=['healthy', 'sick'],\n",
" proportion=True,\n",
" impurity=False,\n",
" filled=True)\n",
"plt.savefig('tree.png',dpi=800)\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "dsaKernel",
"language": "python",
"name": "dsakernel"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}