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{
"cells": [
{
"cell_type": "markdown",
"id": "10d2cf4b",
"metadata": {},
"source": [
"# Assignment 5: Decision Tree Classifier\n",
"Train a decision tree classifier on a synthetic dataset of customer purchases.\n",
"Predict whether a customer will buy based on age and income."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "10abdab6",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"\n",
"# Synthetic dataset\n",
"data = {\n",
" 'age': [25, 30, 35, 40],\n",
" 'income': [50000, 60000, 55000, 70000],\n",
" 'buy': [0, 1, 0, 1]\n",
"}\n",
"df = pd.DataFrame(data)\n",
"\n",
"# Train model\n",
"X = df[['age', 'income']]\n",
"y = df['buy']\n",
"model = DecisionTreeClassifier()\n",
"model.fit(X, y) # Error: Missing arguments, should be model.fit(X, y)\\n\",\n",
"\n",
"# Predict\\n\",\n",
"print(model.predict([[30, 65000]]))"
]
}
],
"metadata": {
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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