from sklearn.datasets import load_irisimport matplotlib.pyplot as pltimport numpy as npimport pandas as pdimport math'''*****************************get datasets****************************'''data2=np.loadtxt('data1.txt')data4 = np.array(data2[:190,[1]])data5 = np.array(data2[:190,[2]])num_train = data4.shape[0]x1 = data4x2 = np.square(data4)x_3 = []for i in data4: j = i ** 3 x_3.append(j)x3 = np.array(x_3)x_4 = []for i in data4: j = i ** 4 x_4.append(j)x4 = np.array(x_4)x_5 = []for i in data4: j = i ** 5 x_5.append(j)x5 = np.array(x_5)x_6 = []for i in data4: j = i ** 6 x_6.append(j)x6 = np.array(x_6)x_7 = []for i in data4: j = i ** 7 x_7.append(j)x7 = np.array(x_7)x_8 = []for i in data4: j = i ** 8 x_8.append(j)x8 = np.array(x_8)x_9 = []for i in data4: j = i ** 9 x_9.append(j)x9 = np.array(x_9)x10 = np.power(data4,1/3)x = np.concatenate([x1,x2,x3,x4,x5,x6,x7,x8,x9,x10],axis=1)y = np.array(data5)print(data2.shape)print(x1.shape)print(x2.shape)p
