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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "e2d9e6fa",
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.metrics import mean_squared_error, r2_score\n",
"\n",
"# Load dataset\n",
"df = sns.load_dataset('mpg')\n",
"df.dropna(inplace=True) # Dropping missing values"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "6eb9757f",
"metadata": {},
"outputs": [],
"source": [
"# Selecting relevant features for simplicity\n",
"features = df[['cylinders', 'displacement', 'horsepower', 'weight', 'acceleration', 'model_year']]\n",
"target = df['mpg']\n",
"\n",
"# Splitting the dataset into training and testing sets\n",
"X_train, X_test, y_train, y_test = train_test_split(features, target, test_size=0.2, random_state=42)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "72821417",
"metadata": {},
"outputs": [],
"source": [
"# Create and train the model\n",
"model = LinearRegression()\n",
"model.fit(X_train, y_train)\n",
"\n",
"# Predictions and Evaluation\n",
"y_pred = model.predict(X_test)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "5dc111db",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: joblib in c:\\users\\user\\anaconda3\\lib\\site-packages (1.2.0)\n"
]
}
],
"source": [
"#!pip install joblib"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c41776ae",
"metadata": {},
"outputs": [],
"source": [
"import joblib"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "318d866d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['mpg_model.pkl']"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Save the model\n",
"joblib.dump(model, 'mpg_model.pkl')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7636f0d3",
"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": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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