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Improve alignment between notebook and book section headers

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Aurélien Geron
2021-10-03 23:05:49 +13:00
parent 6b821335c0
commit 3f89676892
6 changed files with 560 additions and 151 deletions
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130
06_decision_trees.ipynb
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@@ -89,7 +89,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# Training and visualizing"
"# Training and Visualizing a Decision Tree"
]
},
{
@@ -109,6 +109,13 @@
"tree_clf.fit(X, y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**This code example generates Figure 6–1. Iris Decision Tree:**"
]
},
{
"cell_type": "code",
"execution_count": 3,
@@ -130,6 +137,20 @@
"Source.from_file(os.path.join(IMAGES_PATH, \"iris_tree.dot\"))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Making Predictions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code to generate Figure 6–2. Decision Tree decision boundaries**"
]
},
{
"cell_type": "code",
"execution_count": 4,
@@ -181,7 +202,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# Predicting classes and class probabilities"
"# Estimating Class Probabilities"
]
},
{
@@ -206,7 +227,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# High Variance"
"## Regularization Hyperparameters"
]
},
{
@@ -227,6 +248,13 @@
"tree_clf_tweaked.fit(X, y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code to generate Figure 6–8. Sensitivity to training set details:**"
]
},
{
"cell_type": "code",
"execution_count": 8,
@@ -244,9 +272,16 @@
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code to generate Figure 6–3. Regularization using min_samples_leaf:**"
]
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
@@ -271,9 +306,16 @@
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Rotating the dataset also leads to completely different decision boundaries:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
@@ -290,9 +332,16 @@
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code to generate Figure 6–7. Sensitivity to training set rotation**"
]
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
@@ -324,12 +373,19 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# Regression trees"
"# Regression"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's prepare a simple linear dataset:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
@@ -341,9 +397,16 @@
"y = y + np.random.randn(m, 1) / 10"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code example:**"
]
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
@@ -353,9 +416,16 @@
"tree_reg.fit(X, y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code to generate Figure 6–5. Predictions of two Decision Tree regression models:**"
]
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
@@ -400,9 +470,16 @@
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code to generate Figure 6-4. A Decision Tree for regression:**"
]
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
@@ -417,16 +494,23 @@
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"Source.from_file(os.path.join(IMAGES_PATH, \"regression_tree.dot\"))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Code to generate Figure 6–6. Regularizing a Decision Tree regressor:**"
]
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
@@ -512,7 +596,7 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
@@ -530,7 +614,7 @@
},
{
"cell_type": "code",
"execution_count": 20,
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
@@ -548,7 +632,7 @@
},
{
"cell_type": "code",
"execution_count": 21,
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
@@ -562,7 +646,7 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
@@ -585,7 +669,7 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
@@ -618,7 +702,7 @@
},
{
"cell_type": "code",
"execution_count": 24,
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
@@ -645,7 +729,7 @@
},
{
"cell_type": "code",
"execution_count": 25,
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
@@ -673,7 +757,7 @@
},
{
"cell_type": "code",
"execution_count": 26,
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
@@ -685,7 +769,7 @@
},
{
"cell_type": "code",
"execution_count": 27,
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
@@ -703,7 +787,7 @@
},
{
"cell_type": "code",
"execution_count": 28,
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [