题解 | 特征扩展实现

import numpy as np
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import StandardScaler
def feature_scaling(data):
    # 补全代码
    stand = StandardScaler()
    minmax = MinMaxScaler()
    data_stand = stand.fit_transform(data).round(4)
    data_minmax = minmax.fit_transform(data).round(4)
    data_stand1 = data_stand.tolist()
    data_minmax1 = data_minmax.tolist()
    return data_stand1,data_minmax1

# 主程序
if __name__ == "__main__":
    # 输入数组
    data = input()

    # 处理输入
    import ast
    data = ast.literal_eval(data)

    # 调用函数计算
    output = feature_scaling(data)
    
    # 输出结果
    print(output)

1.使用MinMaxScaler，用fit_transform函数

2.array转list,用tolist函数