Description: 通过字段系数赋值，将逻辑回归应用到SQL中-Through field coefficient of assignment, the applications of logistic regression to SQL Platform: |
Size: 3072 |
Author:屎壳郎滚粪球 |
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Description: 逻辑回归，机器学习相关内容，内有说明，基于matlab仿真-ex2.m- Octave script that will help step you through the exercise
ex2 reg.m- Octave script for the later parts of the exercise
ex2data1.txt- Training set for the rst half of the exercise
ex2data2.txt- Training set for the second half of the exercise
submit.m- Submission script that sends your solutions to our servers
mapFeature.m- Function to generate polynomial features
plotDecisionBounday.m- Function to plot classi er s decision boundary
[?] plotData.m- Function to plot 2D classi cation data
[?] sigmoid.m- Sigmoid Function
[?] costFunction.m- Logistic Regression Cost Function
[?] predict.m- Logistic Regression Prediction Function
[?] costFunctionReg.m- Regularized Logistic Regression Cost
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Size: 26624 |
Author:张伟强 |
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Description: 多分类学习及神经网络，机器学习相关，基于matlab计算-ex3.m- Octave script that will help step you through part 1
ex3 nn.m- Octave script that will help step you through part 2
ex3data1.mat- Training set of hand-written digits
ex3weights.mat- Initial weights for the neural network exercise
submitWeb.m- Alternative submission script
submit.m- Submission script that sends your solutions to our servers
displayData.m- Function to help visualize the dataset
fmincg.m- Function minimization routine (similar to fminunc)
sigmoid.m- Sigmoid function
[?] lrCostFunction.m- Logistic regression cost function
[?] oneVsAll.m- Train a one-vs-all multi-class classi er
[?] predictOneVsAll.m- Predict using a one-vs-all multi-class classi er
[?] predict.m- Neural network prediction function Platform: |
Size: 7608320 |
Author:张伟强 |
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Description: lr.py是用python实现了逻辑回归的源代码，并附带有注释。mlp.py是用python实现了多层感知机的源代码，并附带有注释。LeNetConvPoolLayer.py是用python实现了LeNet网络，并附带有注释。该文件需要引用mlp.py。-lr.py is python source code achieving a logistic regression , along with comments. mlp.py realized MLP by python, along with comments. LeNetConvPoolLayer.py used python to realize LeNet network, along with comments. This file needs to reference mlp.py. Platform: |
Size: 27648 |
Author:许联开 |
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Description: 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 Platform: |
Size: 1024 |
Author:梁良 |
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Description: 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 Platform: |
Size: 1024 |
Author:朱致华 |
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Description: 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 can handle the users authentication with predefined user name and password. The proposed framework provides a high level guarantee for protecting sensitive information, since the information exchanged between the server and the client is the posterior distribution of coefficients. Platform: |
Size: 52224 |
Author:wang |
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Description: 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. Platform: |
Size: 2048 |
Author:liuchao |
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Description: 本书第一部分主要介绍机器学习基础，以及如何利用算法进行分类，并逐步介绍了多种经典的监督学习算法，如k近邻算法、朴素贝叶斯算法、Logistic回归算法、支持向量机、AdaBoost集成方法、基于树的回归算法和分类回归树（CART）算法等。第三部分则重点介绍无监督学习及其一些主要算法：k均值聚类算法、Apriori算法、FP-Growth算法。第四部分介绍了机器学习算法的一些附属工具。-
In the first part, mainly introduced the machine learning base, and how to use the algorithm to classify, and gradually introduced the variety of classical supervised learning algorithms such as k-nearest neighbor, naive Bayes algorithm, logistic regression algorithm, support vector machine (SVM) and AdaBoost ensemble method, based on the regression tree algorithm and classification and regression tree (CART) algorithm. The third part focuses on unsupervised learning and some of the main algorithms: K mean clustering algorithm, Apriori algorithm, FP-Growth algorithm. The fourth part introduces some tools of machine learning algorithm. Platform: |
Size: 20149248 |
Author:孙伟 |
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Description: Logistic回归主要目的是寻找一个非线性sigmoid的最佳拟合参数，采用梯度上升算法可以达到局部的最优化-The main purpose of Logistic regression is to find the best fitting parameters of a nonlinear sigmoid, and the gradient ascent algorithm can be used to achieve the local optimization. Platform: |
Size: 1024 |
Author:dongyanyan |
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Description: 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-A comprehensive and systematic introduction to the main methods of statistical learning, particularly supervised learning methods, including Perceptron, k nearest neighbor, naive Bayes method, decision tree, logistic regression and maximum entropy models, support vector machines, lifting scheme, EM algorithm, hidden Markov models and conditions with airports Platform: |
Size: 17750016 |
Author:shishi |
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Description: 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 Platform: |
Size: 1024 |
Author:tiger |
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