跟着Leo机器学习实战：回归

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跟着Leo机器学习实战：回归

目标模型

f(X)=XW

加载数据

from numpy import *
def loadDataSet(fileName):      #general function to parse tab -delimited floats

numFeat = len(open(fileName).readline().split('\t')) - 1 #get number of fields 

dataMat = []; labelMat = []

fr = open(fileName)

for line in fr.readlines():

lineArr =[]

curLine = line.strip().split('\t')

for i in range(numFeat):

lineArr.append(float(curLine[i]))

dataMat.append(lineArr)

labelMat.append(float(curLine[-1]))

return dataMat,labelMat

训练函数，返回权重函数

def standRegres(xArr,yArr):
    xMat = mat(xArr); yMat = mat(yArr).T
    xTx = xMat.T*xMat
    if linalg.det(xTx) == 0.0:
        print ("This matrix is singular, cannot do inverse")
        return
    ws = xTx.I * (xMat.T*yMat)
    return ws