python實現投票整合分類器
阿新 • • 發佈:2019-01-04
匯入相應的模組
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import itertools
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.ensemble import RandomForestClassifier
from mlxtend.classifier import EnsembleVoteClassifier
from mlxtend.data import iris_data
from mlxtend.plotting import plot_decision_regions
初始化分類器
clf1 = LogisticRegression(random_state=0)
clf2 = RandomForestClassifier(random_state=0)
clf3 = SVC(random_state=0, probability=True)
eclf = EnsembleVoteClassifier(clfs=[clf1, clf2, clf3],
weights= [2, 1, 1], voting='soft')
匯入iris資料
X, y = iris_data()
X = X[:,[0, 2]]
畫決策區域
gs = gridspec.GridSpec(2, 2)
fig = plt.figure(figsize=(10, 8))
labels = ['Logistic Regression',
'Random Forest',
'RBF kernel SVM',
'Ensemble']
for clf, lab, grd in zip([clf1, clf2, clf3, eclf],
labels,
itertools.product([0, 1],
repeat=2)):
clf.fit(X, y)
ax = plt.subplot(gs[grd[0], grd[1]])
fig = plot_decision_regions(X=X, y=y,
clf=clf, legend=2)
plt.title(lab)
plt.show()