Description: 机器学习文本分类的SVM算法实现，VC++ 6.0环境下编译-A SVM algorithm for text classification in machine learning, and compiled under the Visual C++ 6.0 environment. Platform: |
Size: 1600512 |
Author:邵云 |
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Description: EM算法估计GMM的matlab版本的源代码，适合给类机器学习问题-EM algorithm estimates GMM Matlab version of the source code, suitable for the type of machine learning problems Platform: |
Size: 3072 |
Author:罗军 |
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Description: 机器学习中的E M算法，本代码是基于高斯混合模型的E M 算法聚类。-machine learning algorithm E M, the code is based on the Gaussian mixture model clustering algorithm E. M. Platform: |
Size: 4096 |
Author:李民 |
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Description: Support Vector Machine is small sample method based on statistic learning theory. It is a new method to deal with the highly nonlinear classification and regression problems .It can better deal with the small sample, nonlinear and -Support Vector Machine is small sample method based on statistic learning theory. It is a new method to deal with the highly nonlinear classification and regression problems. It can better deal with the small sample, nonlinear and Platform: |
Size: 32768 |
Author:张真 |
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Description: 新神经网络
Extreme Learning Machine
比SVM快，附4个例子
-The new neural network Extreme Learning Machine faster than the SVM, with four examples of Platform: |
Size: 869376 |
Author:yu wei |
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Description: 马克斯普朗克提供的机器学习程序包，主要是matlab代码，另外也调用了大量的weka代码和libsvm代码-Provided by the Max Planck Institute for machine learning package, mainly matlab code, also called a large number of weka code and code libsvm Platform: |
Size: 6436864 |
Author:De-Chuan Zhan |
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Description: SVM(Support Vector Machine)指的是支持向量机，是常见的一种判别方法。在机器学习领域，是一个有监督的学习模型，通常用来进行模式识别、分类以及回归分析。
Vapnik等人在多年研究统计学习理论基础上对线性分类器提出了另一种设计最佳准则。其原理也从线性可分说起，然后扩展到线性不可分的情况。甚至扩展到使用非线性函数中去，这种分类器被称为支持向量机(Support Vector Machine，简称SVM)。支持向量机的提出有很深的理论背景。
支持向量机方法是在后来提出的一种新方法。
SVM的主要思想可以概括为两点:
它是针对线性可分情况进行分析，对于线性不可分的情况，通过使用非线性映射算法将低维输入空间线性不可分的样本转化为高维特征空间使其线性可分，从而使得高维特征空间采用线性算法对样本的非线性特征进行线性分析成为可能。
它基于结构风险最小化理论之上在特征空间中构建最优超平面，使得学习器得到全局最优化，并且在整个样本空间的期望以某个概率满足一定上界。(442/5000
SVM(Support Vector Machine) refers to Support Vector Machine, which is a common discriminant method. In the field of machine learning, it is a supervised learning model, which is usually used for pattern recognition, classification and regression analysis.
Vapnik et al. proposed another design criterion for linear classifier on the basis of years of statistical learning theory. The principle is also derived from linear separability, and then extends to linear inseparability. Even extending to the use of nonlinear functions, this classifier is called Support Vector Machine (SVM). The support vector machine has a deep theoretical background.) Platform: |
Size: 633856 |
Author:飛上云端 |
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Description: 这是使用matlab进行机器学习的教程，共分为4个部分。(This is a tutorial for machine learning using MATLAB, which is divided into 4 parts.) Platform: |
Size: 3887104 |
Author:笑。。 |
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Search - Machine Learning matlab