样本平均

样本内的平均

max_index = np.argmax(x,axis=0) # 取每个样本最大值的下标
min_index =np.argmin(x,axis= 0) 
print(len(max_index))
print(x[max_index[0]][0])
for j in range(x.shape[1]):
    d =x[max_index[j]][j]-x[min_index[j]][j]
    # print("num of feature",len(x[0]))
    for i in range(x.shape[0]):
        x[i][j] = (x[i][j]-x[min_index[j]][j])/d

样本间的平均

max_index = np.argmax(x,axis=1) # 取每一行的最大值
min_index =np.argmin(x,axis=1)
for  i in range(x.shape[0]):
    d= x[i][max_index[i]]-x[i][min_index[i]]
    for j in range(x.shape[1]):
        x[i][j]=(x[i][j]-x[i][min_index[i]])/d