hadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM4NjQxOTg1,size_16,color_FFFFFF,t_70)


import numpy as np
import matplotlib.pyplot as plt
from math import sqrt
from sklearn import linear_model
import random


def create_data():
    X=np.array(
        [
        [1,3,3],
        [1,4,3],
        [1,1,1],
        [1,0,2]
            ])
    Y= np.array(
            [
            [1],
            [1],
            [-1],
            [-1]
                ] )
    return X,Y

def update_ws(X,Y,W,lr=0.01):
    V= np.sign(np.dot(X,W))#np.dot(X,W) array矩阵相乘 4*3乘3*1等于4*1
    print (Y)
    W_ =lr*(X.T.dot(Y-V))/int(X.shape[0])#np.dot(X,W) array矩阵相乘 3*4乘4*1等于3*1
    W = W+W_
    return W
    
def main():
    x_,y_=create_data()
    W= (np.random.random([3,1])-0.5)*2
    for i in range(100):
        W= update_ws(x_,y_,W,0.11)
        V_ = np.sign(np.dot(x_,W))
        if(V_ == y_).all():
            print ("epochs = {}".format(i+1));
            break;
    x1 = [3,4]
    y1 = [3,3]

    x2 = [1,0]
    y2 = [1,2]

    k= -W[1]/W[2]
    b= -W[0]/W[2]

    print ("k = {},b= {}".format(k,b));

    x_axis =(0,5)
    plt.plot(x_axis,x_axis*k+b,'r')
    # plt.plot(-1,1,c='g',marker="o")
    plt.scatter(x1,y1,c='b')
    plt.scatter(x2,y2,c='g')

    plt.show()
    
    

    


main()

单层感知机_插入图片


随机生成范围数据

import numpy as np
import matplotlib.pyplot as plt
from math import sqrt
from sklearn import linear_model
import random

def create_data_():#随机创建10个点,这样随机的点未必正确，最好读取数据集，或创建一条直线，分出边界。
    n=5
    x1=(np.random.randint(-5,0,size=(n,3)))
    x2=(np.random.randint(0,5,size=(n,3)))
    y1= (np.random.randint(-1,0,size=[n,1]))
    y2=(np.random.randint(1,2,size=[n,1]))
    Y =np.concatenate((y1,y2),axis=0)#水平组合
    X=np.concatenate((x1,x2),axis=0)#水平组合
    return X,Y
def update_ws(X,Y,W,lr=0.01):
    V= np.sign(np.dot(X,W))#np.dot(X,W) array矩阵相乘 10*3乘3*1等于10*1
    W_ =lr*(X.T.dot(Y-V))/int(X.shape[0])#np.dot(X,W) array矩阵相乘 3*10乘10*1等于3*1
    W = W+W_
    return W
def main():
    x_,y_=create_data_()
    W= (np.random.random([3,1])-0.5)*2
    for i in range(1000):
        W= update_ws(x_,y_,W,0.02)
        V_ = np.sign(np.dot(x_,W))
        if(V_ == y_).all():
            print ("epochs = {}".format(i+1));
            #break;

    
    print ("W = {}.".format(W));
    k= -W[1]/W[2]
    b= -W[0]/W[2]
    print ("k = {},b= {}".format(k,b));
    x_axis =(-5,5)
    count = (len(x_))
    for i in range(count):
        if i<5:
            plt.plot(x_[i][0],x_[i][1],c='b',marker="o")
        else:
            plt.plot(x_[i][0],x_[i][1],c='g',marker="o")
    plt.plot(x_axis,x_axis*k+b,'r')
    plt.show()
    
 
main()

单层感知机_插入图片_02