# -*- coding: UTF-8 -*- import numpy as np import math from collections import Counter import pandas as pd infinity = float(-2 ** 31) ''' 自定义逻辑回归的实现 ''' def sigmodFormatrix(Xb, thetas): params = - Xb.dot(thetas) r = np.zeros(params.shape[0]) # 返回一个np数组 ...
4.python代码实现 代码语言:javascript 代码运行次数:0 运行 AI代码解释 1#-*-coding:utf-8-*-2"""3Created on Wed Feb2411:04:11201645@author:SumaiWong6"""78importnumpyasnp9importpandasaspd10from numpyimportdot11from numpy.linalgimportinv1213iris=pd.read_csv('D:\iris.csv')14dummy=pd.get_dummi...
一模一样,先做dummy coding,然后直接送进回归模型里就行。这里用了数据集里的学生身份和是否违约进行回归 log2 = logit('default_Yes ~ student_Yes', data=df).fit() print(log2.summary()) 回归结果 我们用balance,income和student作为预测变量,default作为响应变量建立多元逻辑斯蒂回归模型,给这个数据集收个...
计算pclass=3的fare均值,因为对pandas使用只是入门,就尝试了数据嵌套获取值,data['pclass']==3,得到第1225条所属pclass同一类数据data[data['pclass']==3.0],再得到这些数据的fare值data[data['pclass']==3.0]["fare"],使用mean()方法求均值。 在《利用python进行数据分析》这本书上,查到了groupby方法,...
线性回归最小二乘和梯度下降法Python代码如下: #-*- coding: utf-8 -*-"""Created on Fri Jan 19 13:29:14 2018 @author: zhang"""importnumpy as npfromsklearn.datasetsimportload_bostonimportmatplotlib.pyplot as pltfromsklearn.cross_validationimporttrain_test_splitfromsklearnimportpreprocessing"""多...
# -*- coding: utf-8 -*- ''' 从0到1Python数据科学之旅 : 讲师csdn学院教学主页: ''' import scipy from scipy.stats import f import numpy as np import matplotlib.pyplot as plt import scipy.stats as stats # additional packages from statsmodels.stats.diagnostic import lillifors ...
4.python代码实现 1#-*- coding: utf-8 -*-2"""3Created on Wed Feb 24 11:04:11 201645@author: SumaiWong6"""78importnumpy as np9importpandas as pd10fromnumpyimportdot11fromnumpy.linalgimportinv1213iris = pd.read_csv('D:\iris.csv')14dummy = pd.get_dummies(iris['Species'])#对Speci...
下面我们开始用 python 自己实现一个简单的 LR 模型。 完整代码可参考:[link] 首先,建立 logistic_regression.py 文件,构建 LR 模型的类,内部实现了其核心的优化函数。 # -*- coding: utf-8 -*-import numpy as npclassLogisticRegression(object): def__init__(self, learning_rate=0.1, max_iter=100, ...
For coding in Python, we utilize thescipy.linalg.pinvfunction to compute Moore-Penrose pseudo inverse and estimate . xMat = np.c_[ np.ones([len(x),1]), x ] #form x matrix from scipy.linalg import pinv theta_estimate = pinv(xMat).dot(y) ...
Logistic Regression in Python Summary - Explore a comprehensive summary of Logistic Regression in Python, covering key concepts, applications, and implementation techniques.