数据分类器详解编程语言

import numpy as np 
 
 
def train_test_split(X, y, test_ratio=0.2, seed=None): 
    """将数据 X 和 y 按照test_ratio分割成X_train, X_test, y_train, y_test""" 
    assert X.shape[0] == y.shape[0], / 
        "the size of X must be equal to the size of y" 
    assert 0.0 <= test_ratio <= 1.0, / 
        "test_ration must be valid" 
 
    if seed: 
        np.random.seed(seed) 
 
    shuffled_indexes = np.random.permutation(len(X)) 
 
    test_size = int(len(X) * test_ratio) 
    test_indexes = shuffled_indexes[:test_size] 
    train_indexes = shuffled_indexes[test_size:] 
 
    X_train = X[train_indexes] 
    y_train = y[train_indexes] 
 
    X_test = X[test_indexes] 
    y_test = y[test_indexes] 
 
    return X_train, X_test, y_train, y_test

from sklearn.model_selection import train_test_split 
X_train,X_test,y_train,y_test = train_test_split(x,y,test_size= 0.2,random_state=666)

from sklearn.neighbors import KNeighborsClassifier 
KNN_classifier = KNeighborsClassifier(n_neighbors=3) 
KNN_classifier.fit(X_train,y_train) 
Y_predict = KNN_classifier.predict(X_test) 
Y_predict

sum(Y_predict==y_test)/len(y_test)