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@NicolasHug
Created December 7, 2019 22:47
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"source": [
"import sklearn\n",
"import numpy as np\n",
"import matplotlib as mpl\n",
"import pandas as pd\n",
"import scipy\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\n",
" max_features=None, max_leaf_nodes=None,\n",
" min_impurity_decrease=0.0, min_impurity_split=None,\n",
" min_samples_leaf=1, min_samples_split=2,\n",
" min_weight_fraction_leaf=0.0, presort='deprecated',\n",
" random_state=0, splitter='best')"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.tree import DecisionTreeRegressor\n",
"from sklearn.datasets import make_regression\n",
"\n",
"X, y = make_regression(n_samples=10, random_state=0, n_features=2, n_informative=2)\n",
"n_samples = 1000\n",
"X = np.arange(n_samples)\n",
"X = np.c_[X, X]\n",
"\n",
"y = np.ones(n_samples)\n",
"y[:100] = 0\n",
"y[:10] = 10\n",
"\n",
"min_samples_leaf = 1\n",
"min_samples_split = 2\n",
"est = DecisionTreeRegressor(random_state=0, min_samples_leaf=min_samples_leaf,\n",
" min_samples_split=min_samples_split)\n",
"\n",
"est.fit(X, y)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.1"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def pdp_fast(est, target_f, x):\n",
" log, exp = np.log, np.exp\n",
" pd = 0\n",
" t = est.tree_\n",
" vals = list()\n",
" def dfs(n, prop):\n",
" nonlocal pd\n",
" if t.children_left[n] == t.children_right[n]:\n",
" pd += prop * t.value[n][0, 0]\n",
" vals.append((prop, t.value[n][0, 0]))\n",
" return\n",
" \n",
" if abs(t.value[n] - 37.596) < .001:\n",
" print(prop)\n",
"\n",
" if t.feature[n] == target_f:\n",
" # follow normal path: either left or right child\n",
" threshold = t.threshold[n]\n",
" child = t.children_left[n] if x <= threshold else t.children_right[n]\n",
" # prop_samples_child = t.weighted_n_node_samples[child] / t.weighted_n_node_samples[n]\n",
" dfs(child, prop)\n",
" else:\n",
" # follow both left and right, with appropriate proportions\n",
" prop_samples_left = t.weighted_n_node_samples[t.children_left[n]] / t.weighted_n_node_samples[n]\n",
" dfs(t.children_left[n], prop * prop_samples_left)\n",
" dfs(t.children_right[n], prop * (1 - prop_samples_left))\n",
"\n",
" dfs(0, prop=1)\n",
" return pd, vals\n",
"\n",
"def pdp_slow(est, target_f, x, X):\n",
" X = X.copy()\n",
" X[:, target_f] = x\n",
" preds = est.predict(X)\n",
" return preds.mean(), preds\n",
"\n",
"target = 0\n",
"x = 1\n",
"pd, vals = pdp_fast(est, target_f=target, x=x)\n",
"pd"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.1"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd_slow, preds = pdp_slow(est, target_f=target, x=x, X=X)\n",
"pd_slow"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"np.set_printoptions(formatter={'float': lambda x:\"{:.2f}\".format(x)})"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0.99, 0.00],\n",
" [0.01, 10.00]])"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"uniques, counts = np.unique(np.array(preds), return_counts=True)\n",
"counts = counts/ counts.sum()\n",
"np.c_[counts, uniques]"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0.99, 0.00],\n",
" [0.01, 10.00]])"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"vals = np.array(vals)\n",
"vals = vals[vals[:, 1].argsort()]\n",
"vals"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from sklearn.tree import plot_tree\n",
"plt.figure(figsize=(10, 10))\n",
"_ = plot_tree(est, )"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'X1')"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"###################\n",
"# Andy, look here #\n",
"###################\n",
"\n",
"\n",
"n_samples = 100\n",
"X_0 = np.random.uniform(-10, 0, size=n_samples)\n",
"i = np.random.choice(n_samples)\n",
"j = np.random.choice(n_samples)\n",
"X_0[i] = 2\n",
"X_0[j] = 2\n",
"\n",
"X_1 = np.random.uniform(-10, 10, size=n_samples)\n",
"X_1[i] = 10\n",
"X_1[j] = 9\n",
"X = np.c_[X_0, X_1]\n",
"\n",
"y = np.empty(X.shape[0])\n",
"y[:] = 0\n",
"y[j] = 1000\n",
"\n",
"plt.scatter(X_0, X_1, c=y)\n",
"plt.gca().set_xlabel('X0')\n",
"plt.gca().set_ylabel('X1', rotation=0)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"tree = DecisionTreeRegressor()\n",
"tree.fit(X, y)\n",
"_ = plot_tree(tree)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"950.0"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"target_f = 0\n",
"x = 2\n",
"pd_slow, preds = pdp_slow(tree, target_f=target_f, x=x, X=X)\n",
"pd_slow"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"500.0"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd_fast, vals = pdp_fast(tree, target_f=target_f, x=x)\n",
"pd_fast"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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