qq_50600845的博客

多分类法 #逻辑回归解决多分类问题 import numpy as np import matplotlib.pyplot as plt import scipy.io as sio from scipy.optimize import minimize#优化函数 data = sio.loadmat('D:\桌面\Coursera-ML-AndrewNg-Notes-master\code\ex3-neural network\ex3data1.mat') #print(data)#字典格式的数据 d

线性可分 #线性可分 import numpy as np import matplotlib.pyplot as plt import pandas as pd def sigmoid(z): return 1/(1+np.exp(-z)) def costFunction(X,Y,theta): inner = sigmoid(X@theta) first = Y * np.log(inner) second = (1-Y) * np.log(1-inner)

单变量 import numpy as np import matplotlib.pyplot as plt import pandas as pd def costFunction(X,Y,theta): inner = np.power((X @ theta - Y),2)#X@theta 等价于X.dot(theta) return np.sum(inner) / (2 * len(X)) def gradientDescent(X,Y,theta,alpha,iters):