ML之回归预测之Lasso:利用Lasso算法对红酒品质wine数据集实现红酒口感评分预测(实数值评分预测)

ML之回归预测之Lasso:利用Lasso算法对红酒品质wine数据集实现红酒口感评分预测(实数值评分预测)


输出结果

设计思路

核心代码

t=3

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

linear_model.lasso_path(X, Y,  return_models=False)
(0)

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