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《统计学习方法》第五章` import math import operator def createDataSet(): labels = ['年龄', "有工作", "有自己的房子", "信贷情况"] dataSet = [["青年", "否", "否", "一般", "否"], ["青年", "否", "否", "好", "否"], ["青年", "是", "否", "好", "是"], ["青年

《统计学习方法》第四章，测试数据同书本一样 trainingData = [ [1, 'S', -1], [1, 'M', -1], [1, 'M', 1], [1, 'S', 1], [1, 'S', -1], [2, 'S', -1], [2, 'M', -1], [2, 'M', 1], [2, 'L', 1], [2, 'L', 1], [3, 'L', 1], [3, 'M', 1], [3, 'M', 1], [3, 'L', 1], [3, 'L', -1] ] #

《统计学习方法》2.3 import numpy as np trainingSet = np.mat([[1, 1], [2, 2], [1, 3], [3, 3], [5, 3], [3, 4]]) y = [1, 1, 1, -1, -1, -1] # 计算Gram矩阵 m = np.shape(trainingSet)[0] GramMatrix = [None] * m for i in range(m): GramMatrix[i] = [0] * m for j in ra

《统计学习方法》2.3感知机学习算法。 # Perceptino感知机 import numpy as np # 训练数据 trainingSet = [np.matrix([3, 3]), np.matrix([4, 3]), np.matrix([1, 1])] ySet = [1, 1, -1] # 参数初始化 eta = 0.1 # 学习率 w = np.matrix([1, 5]) b = 0 count = 0 while count < len(trainingSet):