{ "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": [ "
\n", " | age | \n", "sex | \n", "cp | \n", "trestbps | \n", "chol | \n", "fbs | \n", "restecg | \n", "thalach | \n", "exang | \n", "oldpeak | \n", "slope | \n", "ca | \n", "thal | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "63 | \n", "1 | \n", "1 | \n", "145 | \n", "233 | \n", "1 | \n", "2 | \n", "150 | \n", "0 | \n", "2.3 | \n", "3 | \n", "0.0 | \n", "6.0 | \n", "
1 | \n", "67 | \n", "1 | \n", "4 | \n", "160 | \n", "286 | \n", "0 | \n", "2 | \n", "108 | \n", "1 | \n", "1.5 | \n", "2 | \n", "3.0 | \n", "3.0 | \n", "
2 | \n", "67 | \n", "1 | \n", "4 | \n", "120 | \n", "229 | \n", "0 | \n", "2 | \n", "129 | \n", "1 | \n", "2.6 | \n", "2 | \n", "2.0 | \n", "7.0 | \n", "
3 | \n", "37 | \n", "1 | \n", "3 | \n", "130 | \n", "250 | \n", "0 | \n", "0 | \n", "187 | \n", "0 | \n", "3.5 | \n", "3 | \n", "0.0 | \n", "3.0 | \n", "
4 | \n", "41 | \n", "0 | \n", "2 | \n", "130 | \n", "204 | \n", "0 | \n", "2 | \n", "172 | \n", "0 | \n", "1.4 | \n", "1 | \n", "0.0 | \n", "3.0 | \n", "
DecisionTreeClassifier(max_depth=3)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
DecisionTreeClassifier(max_depth=3)