ML之xgboost：利用xgboost算法(sklearn+3Split)训练mushroom蘑菇数据集(22+1,6513+1611)来预测蘑菇是否毒性(二分类预测)

ML之xgboost：利用xgboost算法(sklearn+3Split)训练mushroom蘑菇数据集(22+1,6513+1611)来预测蘑菇是否毒性(二分类预测)

目录

输出结果

设计思路

核心代码

输出结果

设计思路

核心代码

seed = 7
test_size = 0.33
X_train_part, X_validate, y_train_part, y_validate = train_test_split(X_train, y_train,   
                                                                      test_size=test_size,random_state=seed)


validare_preds = bst.predict(X_validate)

train_accuracy = accuracy_score(y_validate, validate_predictions)
print ("【max_depth=3】Validation Accuary: %.2f%%" % (train_accuracy * 100.0))

标签：3Split,xgboost,train,蘑菇,test,validate,accuracy,size
来源： https://blog.51cto.com/u_14217737/2905661