Created
February 28, 2018 13:13
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2-class 2-D random forest sample with iris dataset
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#!/usr/bin/env python3 | |
#-*- coding: utf-8 -*- | |
import numpy as np | |
import matplotlib.pyplot as plt | |
from sklearn.datasets import load_iris | |
from sklearn.ensemble import RandomForestClassifier | |
from sklearn.tree import export_graphviz | |
export_dot = True | |
iris = load_iris() | |
mask = iris.target != 2 | |
X = iris.data[mask][:,[1,0]] | |
Y = iris.target[mask] | |
xmin, ymin = np.min(X, axis=0) - 0.1 | |
xmax, ymax = np.max(X, axis=0) + 0.1 | |
clf = RandomForestClassifier(n_estimators=4) | |
clf.fit(X, Y) | |
fig, axes = plt.subplots(2, 2) | |
plt.tight_layout(h_pad=0.5, w_pad=0.5, pad=2.5) | |
for i in range(4): | |
ax = axes[i//2, i%2] | |
E = clf.estimators_[i] | |
if export_dot: | |
export_graphviz(E, out_file="tree%d.dot" % i) | |
# run | |
# $ for file in *.dot; do dot -Tpdf $file -o $file.pdf; done | |
# on a bash to generate tree visualization | |
T = E.tree_ | |
n_nodes = T.node_count | |
children_left = T.children_left | |
children_right = T.children_right | |
feature = T.feature | |
threshold = T.threshold | |
values = T.value | |
node_depth = np.zeros(shape=n_nodes, dtype=np.int64) | |
is_leaves = np.zeros(shape=n_nodes, dtype=bool) | |
def plot_boundary(node_id, xmi, xma, ymi, yma): | |
if (children_left[node_id] != children_right[node_id]): | |
thres = threshold[node_id] | |
if feature[node_id] == 0: | |
ax.plot([thres, thres], [ymi, yma], "g-") | |
plot_boundary(children_left[node_id], xmi, thres, ymi, yma) | |
plot_boundary(children_right[node_id], thres, xma, ymi, yma) | |
elif feature[node_id] == 1: | |
ax.plot([xmi, xma], [thres, thres], "g-") | |
plot_boundary(children_left[node_id], xmi, xma, ymi, thres) | |
plot_boundary(children_right[node_id], xmi, xma, thres, yma) | |
else: | |
raise Exception | |
else: | |
color = "r" if np.argmax(values[node_id]) == 1 else "b" | |
ax.add_patch( | |
plt.Rectangle(xy=[xmi, ymi], width=xma-xmi, height=yma-ymi, | |
linewidth=0, alpha=0.2, facecolor=color) | |
) | |
plot_boundary(0, xmin, xmax, ymin, ymax) | |
ax.plot(X[Y==0,0], X[Y==0,1], "b_") | |
ax.plot(X[Y==1,0], X[Y==1,1], "r+") | |
ax.set_xlim((xmin, xmax)) | |
ax.set_ylim((ymin, ymax)) | |
plt.show() |
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