搜索资源列表
LogitTwice
- 基于逻辑回归的二分类算法代码,能很好的实现-Binary logistic regression based algorithm code, can achieve a good
LogitMul
- 基于逻辑回归的多分类问题,可以实现至少三类数据的分类-Classification based on multiple logistic regression, classification can be achieved at least three types of data
1
- 主要是python环境下用来实现lr逻辑回归模型特征分类的源码-The main source is used to achieve lr logistic regression models feature classification under python environment
Shuang_EP_Distributed
- 在客户端和服务器通过套接字连接设计分布式逻辑回归模型。该服务器可以处理用户的使用预定义的用户名和密码验证。该框架提供了用于保护敏感信息的高层次的保证,由于信息服务器之间交换和客户端是系数的后验分布。-We design a distributed logistic regression model using expectation propagation, where clients and server are connected through sockets. The server ca
LogisticRegression
- 本例是用Python写的简单的逻辑回归的例子,可以下载试试。-This case is an example of a simple logistic regression written in Python, you can download a try.
logregmatlab
- matlab实现逻辑回归,梯度上升(效果不好)及牛顿法实现(效果好)-matlab realize logistic regression, gradient ascent (not good) and Newton' s method to achieve
logRegres---python
- 机器学习中的逻辑回归算法,经过测试,可以使用-Logistic regression algorithm of machine learning, through the test, you can use
logRegres
- logistic Regression 实现逻辑回归的一个小例子,值得借鉴和学习。-logistic Regression
Regression
- 实现逻辑回归的c++源码,功能完善,封装完好,能直接运行-Code of logistic regression
IRLS_python
- 逻辑回归python实现代码,并画图比较算法准确度-Logistic regression python implementation code, and drawing comparison algorithm accuracy
knn_logistic_naiveBayes
- 统计机器学习经典分类算法MATLAB代码,付数据集。包括knn算法,逻辑斯蒂回归和朴素贝叶斯算法。-Classical statistical machine learning classification algorithm MATLAB code, pay dataset. Including knn algorithm, logistic regression and naive Bayes algorithm.
Practice2
- 根据学生两次考试成绩的数据来预测学生是否能被大学录取,用逻辑斯蒂回归算法实现,分别执行梯度下降算法、随机梯度下降算法、牛顿法-According student test scores twice to predict whether the student can be admitted to universities, implemented in logistic regression algorithm.
2012.李航.统计学习方法
- 《统计学习方法》是计算机及其应用领域的一门重要的学科。《统计学习方法》全面系统地介绍了统计学习的主要方法,特别是监督学习方法,包括感知机、k近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等。除第1章概论和最后一章总结外,每章介绍一种方法。叙述从具体问题或实例入手,由浅入深,阐明思路,给出必要的数学推导,便于读者掌握统计学习方法的实质,学会运用。为满足读者进一步学习的需要,书中还介绍了一些相关研究,给出了少量习题,列出了主要参考文
高风代码
- 本内容是有关机器学习的包含贝叶斯分类器,随机森林,支持向量机,神经网络,logistic多元回归等(The contents of this paper are machine learning, including Bayesian classifier, random forest, support vector machines, neural network, logistic multiple regression and so on)
data
- 逻辑回归数据集,可以用来测试逻辑回归算法精度,用来调参(logistic regression data set)
IV值计算
- IV值的全称是information value,中文的就是信息量或信息值,其主要作用就是当我们在用决策树或逻辑回归构建分类模型时对变量进行筛选(The full name of IV value is information value. Chinese is information or information value. Its main function is to filter variables when we use decision tree or logistic regre
C1W2L11
- deeplearning.ai 基本的神经 网络编程 对数几率回归(deeplearning.ai Basics of Neural Network Programming Logistic Regression)
R机器学习
- 逻辑回归, GBM, knn, XGB的实现(Logistic regression, GBM, knn, XGB)
预处理.py
- 使用python对数据进行预处理后跑逻辑回归模型(Using Python to preprocess the data, run the logistic regression model.)