模型准确度测算详解编程语言

def accuracy_score(y_true, y_predict): 
    """计算y_true和y_predict之间的准确率""" 
    assert len(y_true) == len(y_predict), / 
        "the size of y_true must be equal to the size of y_predict" 
 
    return np.sum(y_true == y_predict) / len(y_true)

def score(self, X_test, y_test): 
        """根据测试数据集 X_test 和 y_test 确定当前模型的准确度""" 
 
        y_predict = self.predict(X_test) 
        return accuracy_score(y_test, y_predict)

from sklearn.metrics import accuracy_score #测试准确度 
accuracy_score(y_test,Y_predict)

from sklearn.model_selection import train_test_split 
from sklearn.neighbors import KNeighborsClassifier 
from sklearn import datasets 
 
digits = datasets.load_digits() 
X = digits.data 
y = digits.target 
 
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size= 0.2,random_state=666) 
 
KNN_classifier = KNeighborsClassifier(n_neighbors=3) 
KNN_classifier.fit(X_train,y_train) 
KNN_classifier.score(X_test,y_test)