Python |
from sklearn.ensemble import RandomForestClassifier;
import sklearn.datasets as datasets;
from sklearn.model_selection import train_test_split;
import numpy as np
ds = datasets.load_iris();
X = ds.data;
y = ds.target ;
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state=14);
clf = RandomForestClassifier(); #建立随机森林分类器
clf = clf.fit(X_train, y_train); #模型训练
y_predicted = clf.predict(X_test); #模型预测
accuracy = np.mean(y_predicted == y_test); #计算准确率
print ("y_test\n",y_test);
print ("y_predicted\n",y_predicted);
print ("accuracy:",accuracy); |