ML之迴歸預測之Lasso：利用Lasso演算法解決迴歸(實數值評分預測)問題—採用10折交叉驗證(測試集error)來評估LassoCV模型

輸出結果

設計思路

核心程式碼

if t==1:
    X = numpy.array(xList)         #Unnormalized X's
    # X = numpy.array(xNormalized)   #Normlized Xss
    Y = numpy.array(labels)          #Unnormalized labels
    # Y = numpy.array(labelNormalized) #normalized lables
elif t==2:
    X = numpy.array(xList)           #Unnormalized X's
    X = numpy.array(xNormalized)     #Normlized Xss
    Y = numpy.array(labels)          #Unnormalized labels
    Y = numpy.array(labelNormalized) #normalized lables
elif t==3:
    X = numpy.array(xList)           #Unnormalized X's
    X = numpy.array(xNormalized)     #Normlized Xss
    Y = numpy.array(labels)          #Unnormalized labels
    # Y = numpy.array(labelNormalized) #normalized lables