Python实现线性逻辑回归和非线性逻辑回归

rubyw

已于 2024-02-21 09:12:52 修改

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分类专栏：机器学习文章标签： python 逻辑回归开发语言机器学习算法

于 2024-02-20 16:29:03 首次发布

本文链接：https://blog.youkuaiyun.com/rubyw/article/details/136193341

线性逻辑回归

# -*- coding: utf-8 -*-
"""
Created on 2024.2.20

@author: rubyw
"""

import matplotlib.pyplot as plt
import numpy as np
from sklearn.metrics import classification_report
from sklearn import preprocessing
from sklearn import linear_model

# 数据是否需要标准化
scale = False

# 载入数据
data = np.genfromtxt('data.csv', delimiter=",")
x_data = data[:, :-1]
y_data = data[:, -1]


def plot():
    x0 = []
    x1 = []
    y0 = []
    y1 = []
    # 切分不同类别的数据
    for i in range(len(x_data)):
        if y_data[i] == 0:
            x0.append(x_data[i, 0])
            y0.append(x_data[i, 1])
        else:
            x1.append(x_data[i, 0])
            y1.append(x_data[i, 1])

    # 画图
    scatter0 = plt.scatter(x0, y0,