day57-elasticnet-regression/elastic-net-regression.ipynb

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   "id": "71e28874",
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   "source": [
    "from sklearn.datasets import load_diabetes\n",
    "from sklearn.linear_model import LinearRegression,Ridge,Lasso,ElasticNet\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "284ccf3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "X,y = load_diabetes(return_X_y=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "799d9080",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state=2)"
   ]
  },
  {
   "cell_type": "code",
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     "execution_count": 73,
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   "source": [
    "# Linear Regression\n",
    "reg = LinearRegression()\n",
    "reg.fit(X_train,y_train)\n",
    "y_pred = reg.predict(X_test)\n",
    "r2_score(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
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     "execution_count": 74,
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   "source": [
    "# Ridge \n",
    "reg = Ridge(alpha=0.1)\n",
    "reg.fit(X_train,y_train)\n",
    "y_pred = reg.predict(X_test)\n",
    "r2_score(y_test,y_pred)"
   ]
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   "cell_type": "code",
   "execution_count": 75,
   "id": "b6b53e7c",
   "metadata": {},
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     "execution_count": 75,
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   "source": [
    "# Lasso\n",
    "reg = Lasso(alpha=0.01)\n",
    "reg.fit(X_train,y_train)\n",
    "y_pred = reg.predict(X_test)\n",
    "r2_score(y_test,y_pred)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 76,
   "id": "5fc65b12",
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     "execution_count": 76,
     "metadata": {},
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   ],
   "source": [
    "# ElasticNet\n",
    "reg = ElasticNet(alpha=0.005,l1_ratio=0.9)\n",
    "reg.fit(X_train,y_train)\n",
    "y_pred = reg.predict(X_test)\n",
    "r2_score(y_test,y_pred)"
   ]
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