Python 中的降维
Jeroen Boeye
Head of Machine Learning, Faktion
将要预测的特征与用于训练的特征分开。
y = house_df['City'] X = house_df.drop('City', axis=1)
进行 70% 训练 / 30% 测试 划分
from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
创建支持向量机分类器并拟合训练数据
from sklearn.svm import SVC svc = SVC() svc.fit(X_train, y_train)
from sklearn.metrics import accuracy_score print(accuracy_score(y_test, svc.predict(X_test)))
0.826
print(accuracy_score(y_train, svc.predict(X_train)))
0.832
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