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Sync notebook 04 with book code

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Aurélien Geron 2021-11-10 17:58:42 +13:00
parent bac934811a
commit 77da622124
1 changed files with 9 additions and 6 deletions
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15
04_training_linear_models.ipynb
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@ -205,6 +205,8 @@
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"plt.figure(figsize=(6, 4)) # not in the book\n",
"plt.plot(X_new, y_predict, \"r-\", label=\"Predictions\")\n",
"plt.plot(X, y, \"b.\")\n",
@ -1052,14 +1054,14 @@
"metadata": {},
"outputs": [],
"source": [
"# not in the book\n",
"\n",
"np.random.seed(42)\n",
"m = 100\n",
"X = 6 * np.random.rand(m, 1) - 3\n",
"y = 0.5 * X ** 2 + X + 2 + np.random.randn(m, 1)\n",
"# X_train, X_val, y_train, y_val = train_test_split(\n",
"# X[:50], y[:50].ravel(), test_size=0.5, random_state=10)\n",
"X_train, y_train = X[:50], y[:50, 0]\n",
"X_valid, y_valid = X[50:], y[50:, 0]"
"X_train, y_train = X[: m // 2], y[: m // 2, 0]\n",
"X_valid, y_valid = X[m // 2 :], y[m // 2 :, 0]"
]
},
{
@ -1070,6 +1072,7 @@
"source": [
"from copy import deepcopy\n",
"from sklearn.metrics import mean_squared_error\n",
"from sklearn.preprocessing import StandardScaler\n",
"\n",
"preprocessing = make_pipeline(PolynomialFeatures(degree=90, include_bias=False),\n",
" StandardScaler())\n",
@ -1192,7 +1195,7 @@
"metadata": {},
"outputs": [],
"source": [
"print(iris.data.head())"
"iris.data.head(3)"
]
},
{
@ -1201,7 +1204,7 @@
"metadata": {},
"outputs": [],
"source": [
"iris.target.head() # note that the instances are not shuffled"
"iris.target.head(3) # note that the instances are not shuffled"
]
},
{