[AI]/python.sklearn
sklearn.ensemble.RandomForestClassifier.2 feature for visualization
givemebro
2020. 4. 20. 15:01
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https://broscoding.tistory.com/160
머신러닝.RandomForestClassifier.기초
import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from sklearn.datasets import load_breast_cancer cancer=load_breast_cancer() X_train,X_test,y_t..
broscoding.tistory.com
X=cancer.data[:,[0,1]]
y=cancer.target
X_train,X_test,y_train,y_test=train_test_split(X,y)
model=RandomForestClassifier(n_estimators=100,max_features='auto')
model.fit(X_train,y_train)
import mglearn
plt.figure(figsize=[12,10])
mglearn.plots.plot_2d_classification(model,X)
mglearn.discrete_scatter(X[:,0],X[:,1],y,alpha=0.3)
plt.figure(figsize=[12,10])
for i in range(5):
plt.subplot(2,3,i+1)
mglearn.plots.plot_tree_partition(X,y,model.estimators_[i])
plt.subplot(2,3,6)
mglearn.plots.plot_2d_classification(model,X)
mglearn.discrete_scatter(X[:,0],X[:,1],y,alpha=0.3)
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