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Tree experiments
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Example on the bananas dataset" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"\n", | |
"SMALL_SIZE = 12\n", | |
"MEDIUM_SIZE = 20\n", | |
"BIGGER_SIZE = 24\n", | |
"\n", | |
"plt.rc('font', size=SMALL_SIZE) # controls default text sizes\n", | |
"plt.rc('axes', titlesize=MEDIUM_SIZE) # fontsize of the axes title\n", | |
"plt.rc('axes', labelsize=MEDIUM_SIZE) # fontsize of the x and y labels\n", | |
"plt.rc('xtick', labelsize=SMALL_SIZE) # fontsize of the tick labels\n", | |
"plt.rc('ytick', labelsize=SMALL_SIZE) # fontsize of the tick labels\n", | |
"plt.rc('legend', fontsize=SMALL_SIZE) # legend fontsize\n", | |
"plt.rc('figure', titlesize=BIGGER_SIZE) # fontsize of the figure title\n", | |
"\n", | |
"%matplotlib inline\n", | |
"%config InlineBackend.figure_format = 'retina'" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"%run fast_trees.py" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"from sklearn import datasets\n", | |
"from sklearn import preprocessing\n", | |
"\n", | |
"banana = datasets.fetch_openml('banana')\n", | |
"X = banana['data']\n", | |
"X = preprocessing.minmax_scale(X)\n", | |
"Y = preprocessing.LabelEncoder().fit_transform(banana['target'])" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"scikit-learn." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
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| |
"text/plain": [ | |
"<Figure size 1080x360 with 6 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 330, | |
"width": 901 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"from mpl_toolkits.axes_grid1 import ImageGrid\n", | |
"import numpy as np\n", | |
"from sklearn import ensemble\n", | |
"from sklearn import tree\n", | |
"\n", | |
"n_cols = 3\n", | |
"fig = plt.figure(figsize=(5 * n_cols, 5))\n", | |
"grid = ImageGrid(\n", | |
" fig, 111,\n", | |
" nrows_ncols=(1, n_cols),\n", | |
" axes_pad=0.5,\n", | |
")\n", | |
"\n", | |
"# Scatter observations\n", | |
"ax = grid[0]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.scatter(X[:, 0], X[:, 1], color=plt.cm.coolwarm(Y.astype(float)), marker='+', s=12)\n", | |
"ax.set_title('Training set', fontsize=16)\n", | |
"ax.set_xlabel(r'$x_1$')\n", | |
"ax.set_ylabel(r'$x_2$')\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Decision tree\n", | |
"clf = tree.DecisionTreeClassifier(max_depth=7, random_state=42)\n", | |
"clf = clf.fit(X, Y)\n", | |
"h = .005\n", | |
"xx, yy = np.meshgrid(np.arange(0, 1, h), np.arange(0, 1, h))\n", | |
"y_pred = clf.predict_proba(np.vstack((xx.ravel(), yy.ravel())).T)[:, 1]\n", | |
"ax = grid[1]\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Decision function with 1 tree', fontsize=16)\n", | |
"ax.set_xlabel(r'$x_1$')\n", | |
"ax.set_ylabel(r'$x_2$')\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Random forest\n", | |
"clf = ensemble.RandomForestClassifier(n_estimators=10, max_depth=7, random_state=42)\n", | |
"clf = clf.fit(X, Y)\n", | |
"y_pred = clf.predict_proba(np.vstack((xx.ravel(), yy.ravel())).T)[:, 1]\n", | |
"ax = grid[2]\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Decision function with 10 trees', fontsize=16)\n", | |
"ax.set_xlabel(r'$x_1$')\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"for ext in ('pdf', 'pgf'):\n", | |
" fig.savefig(f'figures/batch.{ext}', bbox_inches='tight')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Uniform random trees." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"model = FastTreesRegressor(n_trees=10, height=7, padding=0., predict_method='leaf', seed=42)\n", | |
"\n", | |
"for x, y in zip(X, Y):\n", | |
" \n", | |
" # Convert to a dictionary\n", | |
" x = dict(enumerate(x))\n", | |
" \n", | |
" model.fit_one(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 720x360 with 4 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 353, | |
"width": 630 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"n_cols = 2\n", | |
"fig = plt.figure(figsize=(5 * n_cols, 5))\n", | |
"grid = ImageGrid(\n", | |
" fig, 111,\n", | |
" nrows_ncols=(1, n_cols),\n", | |
" axes_pad=0.5,\n", | |
")\n", | |
"\n", | |
"# Decision function of first tree\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_one(x, tree_num=0)\n", | |
"\n", | |
"ax = grid[0]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Single tree', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_ylabel(r'$x_2$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Overall decision function\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_one(x)\n", | |
"ax = grid[1]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title(f'{len(model.trees)} trees', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"for ext in ('pdf', 'pgf'):\n", | |
" fig.savefig(f'figures/uniform_moons.{ext}', bbox_inches='tight')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Centered random trees." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"model = FastTreesRegressor(n_trees=10, height=7, padding=0.5, predict_method='leaf', seed=42)\n", | |
"\n", | |
"for x, y in zip(X, Y):\n", | |
" \n", | |
" # Convert to a dictionary\n", | |
" x = dict(enumerate(x))\n", | |
" \n", | |
" model.fit_one(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 720x360 with 4 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 353, | |
"width": 630 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"n_cols = 2\n", | |
"fig = plt.figure(figsize=(5 * n_cols, 5))\n", | |
"grid = ImageGrid(\n", | |
" fig, 111,\n", | |
" nrows_ncols=(1, n_cols),\n", | |
" axes_pad=0.5,\n", | |
")\n", | |
"\n", | |
"# Decision function of first tree\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_one(x, tree_num=0)\n", | |
"\n", | |
"ax = grid[0]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Single tree', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_ylabel(r'$x_2$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Overall decision function\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_one(x)\n", | |
"ax = grid[1]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title(f'{len(model.trees)} trees', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"for ext in ('pdf', 'pgf'):\n", | |
" fig.savefig(f'figures/centered_moons.{ext}', bbox_inches='tight')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Us." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"model = FastTreesRegressor(n_trees=10, height=7, padding=0.2, predict_method='leaf', seed=42)\n", | |
"\n", | |
"for x, y in zip(X, Y):\n", | |
" \n", | |
" # Convert to a dictionary\n", | |
" x = dict(enumerate(x))\n", | |
" \n", | |
" model.fit_one(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 10, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
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\n", | |
"text/plain": [ | |
"<Figure size 720x360 with 4 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 353, | |
"width": 630 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"from mpl_toolkits.axes_grid1 import ImageGrid\n", | |
"import numpy as np\n", | |
"from sklearn import ensemble\n", | |
"from sklearn import tree\n", | |
"\n", | |
"n_cols = 2\n", | |
"fig = plt.figure(figsize=(5 * n_cols, 5))\n", | |
"grid = ImageGrid(\n", | |
" fig, 111,\n", | |
" nrows_ncols=(1, n_cols),\n", | |
" axes_pad=0.5,\n", | |
")\n", | |
"\n", | |
"# Decision function of first tree\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_one(x, tree_num=0)\n", | |
"\n", | |
"ax = grid[0]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Single tree', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_ylabel(r'$x_2$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Overall decision function\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_one(x)\n", | |
"ax = grid[1]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title(f'{len(model.trees)} trees', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"for ext in ('pdf', 'pgf'):\n", | |
" fig.savefig(f'figures/moons.{ext}', bbox_inches='tight')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Hoeffding." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 12, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"from creme import compat\n", | |
"from creme import ensemble\n", | |
"from skmultiflow import trees\n", | |
"\n", | |
"model = compat.SKL2CremeClassifier(\n", | |
" trees.HoeffdingTree(leaf_prediction='mc', grace_period=100, split_confidence=1e-2),\n", | |
" n_features=2,\n", | |
" classes=[False, True]\n", | |
")\n", | |
"model = ensemble.BaggingClassifier(model, n_models=10)\n", | |
"\n", | |
"for x, y in zip(X, Y):\n", | |
" x = dict(enumerate(x))\n", | |
" model.fit_one(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 13, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 720x360 with 4 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 353, | |
"width": 630 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"n_cols = 2\n", | |
"fig = plt.figure(figsize=(5 * n_cols, 5))\n", | |
"grid = ImageGrid(\n", | |
" fig, 111,\n", | |
" nrows_ncols=(1, n_cols),\n", | |
" axes_pad=0.5,\n", | |
")\n", | |
"\n", | |
"# Decision function of first tree\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model[0].predict_proba_one(x)[True]\n", | |
"\n", | |
"ax = grid[0]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Single tree', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_ylabel(r'$x_2$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Overall decision function\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_proba_one(x)[True]\n", | |
" \n", | |
"ax = grid[1]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title(f'{len(model)} trees', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"for ext in ('pdf', 'pgf'):\n", | |
" fig.savefig(f'figures/hoeffding_moons.{ext}', bbox_inches='tight')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Mondrian." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 14, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import sys\n", | |
"\n", | |
"sys.path.append('scikit-garden')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/Users/mhalford/opt/anaconda3/envs/fast-trees/lib/python3.7/site-packages/sklearn/utils/deprecation.py:144: FutureWarning: The sklearn.ensemble.forest module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.ensemble. Anything that cannot be imported from sklearn.ensemble is now part of the private API.\n", | |
" warnings.warn(message, FutureWarning)\n", | |
"/Users/mhalford/opt/anaconda3/envs/fast-trees/lib/python3.7/site-packages/sklearn/externals/joblib/__init__.py:15: FutureWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n", | |
" warnings.warn(msg, category=FutureWarning)\n", | |
"/Users/mhalford/opt/anaconda3/envs/fast-trees/lib/python3.7/site-packages/sklearn/externals/six.py:31: FutureWarning: The module is deprecated in version 0.21 and will be removed in version 0.23 since we've dropped support for Python 2.7. Please rely on the official version of six (https://pypi.org/project/six/).\n", | |
" \"(https://pypi.org/project/six/).\", FutureWarning)\n", | |
"/Users/mhalford/opt/anaconda3/envs/fast-trees/lib/python3.7/site-packages/sklearn/utils/deprecation.py:144: FutureWarning: The sklearn.tree.tree module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.tree. Anything that cannot be imported from sklearn.tree is now part of the private API.\n", | |
" warnings.warn(message, FutureWarning)\n" | |
] | |
} | |
], | |
"source": [ | |
"import skgarden\n", | |
"\n", | |
"model = compat.SKL2CremeClassifier(\n", | |
" skgarden.MondrianTreeClassifier(),\n", | |
" n_features=2,\n", | |
" classes=[False, True]\n", | |
")\n", | |
"model = ensemble.BaggingClassifier(model, n_models=10)\n", | |
"\n", | |
"for x, y in zip(X, Y):\n", | |
" x = dict(enumerate(x))\n", | |
" model.fit_one(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 16, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
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| |
"text/plain": [ | |
"<Figure size 720x360 with 4 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 353, | |
"width": 630 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"n_cols = 2\n", | |
"fig = plt.figure(figsize=(5 * n_cols, 5))\n", | |
"grid = ImageGrid(\n", | |
" fig, 111,\n", | |
" nrows_ncols=(1, n_cols),\n", | |
" axes_pad=0.5,\n", | |
")\n", | |
"\n", | |
"# Decision function of first tree\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model[0].predict_proba_one(x)[True]\n", | |
"\n", | |
"ax = grid[0]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Single tree', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_ylabel(r'$x_2$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Overall decision function\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_proba_one(x)[True]\n", | |
" \n", | |
"ax = grid[1]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title(f'{len(model)} trees', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"for ext in ('pdf', 'pgf'):\n", | |
" fig.savefig(f'figures/mondrian_moons.{ext}', bbox_inches='tight')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"AMF." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 17, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import numpy as np\n", | |
"import onelearn\n", | |
"\n", | |
"class AMFClassifier(onelearn.AMFClassifier):\n", | |
" \n", | |
" def predict_proba(self, X, *args, **kwargs):\n", | |
" X = np.array(X)\n", | |
" try:\n", | |
" return super().predict_proba(X, *args, **kwargs)\n", | |
" except RuntimeError:\n", | |
" return np.array([np.array([])])\n", | |
" \n", | |
" def partial_fit(self, X, y, *args, **kwargs):\n", | |
" X = np.array(X)\n", | |
" y = np.array(y)\n", | |
" return super().partial_fit(X, y, *args, **kwargs)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 25, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"model = compat.SKL2CremeClassifier(\n", | |
" AMFClassifier(n_estimators=10, n_classes=2),\n", | |
" n_features=2,\n", | |
" classes=[False, True]\n", | |
")\n", | |
"\n", | |
"for x, y in zip(X, Y):\n", | |
" x = dict(enumerate(x))\n", | |
" model.fit_one(x, y)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 33, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([[0.03846154, 0.96153843]], dtype=float32)" | |
] | |
}, | |
"execution_count": 33, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"model.sklearn_estimator.predict_proba_tree([x], 0)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 28, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"{0: 0.0, 1: 0.0}" | |
] | |
}, | |
"execution_count": 28, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"x" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 35, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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| |
"text/plain": [ | |
"<Figure size 720x360 with 4 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 353, | |
"width": 630 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"n_cols = 2\n", | |
"fig = plt.figure(figsize=(5 * n_cols, 5))\n", | |
"grid = ImageGrid(\n", | |
" fig, 111,\n", | |
" nrows_ncols=(1, n_cols),\n", | |
" axes_pad=0.5,\n", | |
")\n", | |
"\n", | |
"# Decision function of first tree\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" y_pred[i] = model.sklearn_estimator.predict_proba_tree([x], 0)[0][1]\n", | |
"\n", | |
"ax = grid[0]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title('Single tree', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_ylabel(r'$x_2$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"# Overall decision function\n", | |
"for i, x in enumerate(np.vstack((xx.ravel(), yy.ravel())).T):\n", | |
" x = dict(enumerate(x))\n", | |
" y_pred[i] = model.predict_proba_one(x)[True]\n", | |
" \n", | |
"ax = grid[1]\n", | |
"ax.grid(alpha=.5)\n", | |
"ax.contourf(xx, yy, y_pred.reshape(xx.shape), cmap=plt.cm.coolwarm, corner_mask=False)\n", | |
"ax.set_title(f'{model.sklearn_estimator.n_estimators} trees', pad=12)\n", | |
"ax.set_xlabel(r'$x_1$', labelpad=12)\n", | |
"ax.set_aspect('equal', 'box')\n", | |
"ax.spines['top'].set_visible(False)\n", | |
"ax.spines['right'].set_visible(False)\n", | |
"ax.set_xlim(-0.05, 1.05)\n", | |
"ax.set_ylim(-0.05, 1.05)\n", | |
"\n", | |
"for ext in ('pdf', 'pgf'):\n", | |
" fig.savefig(f'figures/amf_moons.{ext}', bbox_inches='tight')" | |
] | |
}, | |
{ | |
"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": 4 | |
} |
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