import sklearn
import numpy as np
from sklearn.neighbors import KNeighborsClassifier
import sklearn.datasets as data

if __name__ == '__main__':
    x_train = [[192,90,46],[180,80,44],[160,45,36],[170,65,41],[154,41,34],[165,60,40]]
    y_train = ["boy","boy","girl","boy","girl","boy"]
    KNN = KNeighborsClassifier(n_neighbors=3)
    KNN.fit(x_train,y_train)
    print(KNN.predict([[155, 45, 35],[175,70,42]]))
    print(range(1, 10)[::2][1])

Python预测蓝蝴蝶：

import sklearn
import numpy as np
from sklearn.neighbors import KNeighborsClassifier
import sklearn.datasets as data
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

if __name__ == '__main__':
    iris = data.load_iris()
    x_train = iris.data
    y_train = iris.target
    KNN = KNeighborsClassifier()
    KNN.fit(x_train,y_train)
    print(KNN.predict(x_train))
    print(y_train)
    print(KNN.score(x_train, y_train))
    cMap = ListedColormap(["#FF0000","#00FF00","#0000FF"])
    plt.scatter(x_train[:,2],x_train[:,3])
    plt.scatter(x_train[:,2],x_train[:,3],c=iris.target,cmap=cMap)
    print(iris.target)

    # plt.plot(x_train[:,1],y_train)
    # plt.plot(x_train[:,2],y_train)
    # plt.plot(x_train[:,3],y_train)
    # plt.plot(x_train[:,0],y_train)
    plt.plot(x_train, y_train)
    plt.show()
    print(x_train)
    print(y_train)