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高斯过程算法在回归和分类中的应用程序。与书本《基于高斯过程的机器学习》配套。本程序是最新的v3.1版，更新于2010-09-27-Gaussian process regression and classification algorithm in the application. And the book " machine learning based on Gaussian process" support. This program is the latest v3.1
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Locally weighted polynomial regression LWPR is a popular instance based al gorithm for learning continuous non linear mappings For more than two or three in puts and for more than a few thousand dat apoints the computational expense of pre dic
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广义回归神经网络是RBF的一个扩展。但是具体怎么实现却代码很少，本代码是一个grnn很好的学习例子。-Generalized regression neural network is an extension of RBF. But how to achieve specific code but rarely, the code is a good learning example grnn.
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GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Ex
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Mixture of linear regressors. The routines contained in this file allow inference and learning of a mixture of linear-Gaussian regression models. Learning is performed by maximizing the data likelihood via the expectation maximization algorithm.
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泛化回归神经网络GRNN(generalized regression NN)应用实例，适合学习使用。-Generalized regression neural network GRNN (generalized regression NN) application examples for learning to use.
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线性回归的学习算法。包括数据分析、线性回归、在线梯度下降、多项式回归。压缩包中给出.txt数据文件及说明文档。-Linear regression learning algorithm. Including data analysis, linear regression line gradient descent, polynomial regression. Compressed data given .txt file and documentation.
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一个回归学习的matlab例程，可以直接运行，具体内容参考图书《视觉机器学习20讲》-A return to learn the Matlab routines, can be run directly, the specific content of reference books < visual machine learning 20
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机器学习中的一种对数据进行分类的模型，非常好用，可以运行，推荐下载。(A machine learning model for data classification, very easy to use, you can run, it is recommended to download.)
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三种梯度下降的logistic regression机器学习入门代码(three logistic regression methods for machine learning)
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linear regression for machine learning lesson
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Logistic Regression for machine learning lessons
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在这个练习中，您将实现线性回归，并看到它在数据上工作。在开始这个编程练习之前，我们强烈建议观看视频讲座，并完成相关主题的复习题。开始锻炼，你将需要下载的启动代码，解压其内容目录到你希望完成练习。如果需要的话，在开始练习之前，使用八度/ matlab中的cd命令改变这个目录。你也可以?ND指示在“环境设置说明”的课程网站安装倍频/ MATLAB。(In this exercise, you will implement linear regression and get to see it wor
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初次接触机器学习，所要知道的一些经典算法(First contact machine learning, some classical algorithms to know)
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machine learning logestic regrassion second code
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classfication and regression tree
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Standford machine-learning 网课第一周编程作业，线性回归的算法实现。(Standford machine-learning method first week of programming operations, the realization of the linear regression algorithm.)
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线性回归梯度下降法程序，用python实现adagrad梯度下降法(Linear regression gradient descent method, using Python to achieve adagrad gradient descent method.)
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通过训练样本使用对数几率回归模型建模，并对测试样本类别进行预测(The training samples are modeled by log likelihood regression model, and then predicts the categories of test samples.)
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用于深度学习 循环神经网络等，方法是分类与回归(Classification and regression of deep learning)
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