文章目录
sklearn learn
代码语言：javascript
复制# -*- coding:utf-8 -*-
# /usr/bin/python
import matplotlib.pyplot as plt
import numpy as np
a = [[1,2,3,4],[2,3,4,5],[3,4,5,6],]
b = [2,2,2,2]
c = np.multiply(a,b)
print(c,type(c))
b1 = [[2],[2],[3],[4]]
c = np.dot(a,b1)
print(c,type(c))
from sklearn.datasets import load_boston
from sklearn.linear_model import LinearRegression,SGDRegressor, Ridge, LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import mean_squared_error, classification_report
from sklearn.externals import joblib
import pandas as pd
import numpy as np
def mylinear():
"""
线性回归直接预测房子价格
:return: None
"""
# 获取数据
lb = load_boston()
# 分割数据集到训练集和测试集
x_train, x_test, y
