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Description: Put simply, SVMpython is SVMstruct, except that all of the C API functions that the user normally has to implement (except those dealing with C specific problems) instead call a function of the same name in a Python module. You can write an SVMstruct instance in Python without having to author any C code. SVMpython tries to stay close to SVMstruct in naming convensions and other behavior, but knowledge of SVMstruct's original C implementation is not required.
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Author: superbear |
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Description: This document contains a general overview in the first few sections as well as a more detailed reference in later sections for SVMpython. If you re already familiar with SVMpython, it s possible to get a pretty good idea of how to use the package merely by browsing through svmstruct.py and multiclass.py. This document provides a more in depth view of how to use the package.
Note that this is not a conversion of SVMstruct to Python. It is merely an embedding of Python in existing C code. All code other than the user implemented API functions is still in C, including optimization.
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Author: 王强 |
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Description: 支持向量机初学者可以看看,用于可以用于C-SVM分类、?-SVM分类、?-SVM回归和?-SVM回归等问题
-Support Vector Machine beginners can see that can be used for C-SVM classification,?-SVM classification,?-SVM regression and?-SVM regression problem
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Size: 827392 |
Author: 无为 |
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Description: 一款不错的支持向量机程序,程序执行效率很高!-A good support vector machine procedures, procedures for the implementation of very efficient!
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Size: 294912 |
Author: myname |
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Description: 这是支持向量机的程序。也是关于svm的,可以很好的学习支持向量机-This is a support vector machine procedure. Is also about the SVM can be good learning support vector machines
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Size: 13133824 |
Author: zhouli |
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Description: SVM回归中用的gridregression.py函数,用它来进行参数寻优,做了一些改动适用于windows。-SVM regression using the gridregression.py function, use it to carry out parameter optimization, has done some changes to apply to windows.
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Size: 3072 |
Author: wangpw |
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Description: 在PYTHON里面,采用LIBSVM,实现对TE数据的多类故障的分类。-In PYTHON inside, using LIBSVM, TE data to realize the classification of many types of failures.
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Size: 482304 |
Author: Sophiehxq |
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Description: Python编写的SVM算法,SVM算法的实现,适合直接使用,开放源代码,Supported Vector Machine。-Python code SVM algorithm,SVM algorithm realizition,easy to use,open source,Supported Vector Machine。
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Size: 35840 |
Author: 王天路 |
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Description: 这是一款基于java和python实现svm支持向量机的算法源代码,可以实现对任意点阵的分类,效果非常明显-This is a based on java and python svm support vector machine algorithm source code, you can achieve the classification of any dot matrix, the effect is very obvious
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Size: 707584 |
Author: 怪兽 |
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Description: python,svm支持向量机例子。里面有文档和源码。-python, svm support vector machine example. There are documents and source code.
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Author: 方奕凯 |
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Description: 用Python写的关于SVM算法的人脸识别小程序(Written in Python on the SVM algorithm for face recognition applet)
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Size: 1024 |
Author: 逆光成影
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Description: Python语言实现的SVM手写数字识别(SVM handwritten numeral recognition based on Python language)
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Size: 172032 |
Author: wuxia
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Description: 用svm算法实现手写识别,核函数使用径向基核函数(Handwritten recognition using SVM algorithm)
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Size: 8192 |
Author: aneybaby727
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Description: 采用SVM算法,用python语言实现的分类识别,可用于异常检测等二分类(Using SVM algorithm, using python language to achieve the classification of identification, can be used for abnormal detection and other two categories)
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Size: 147456 |
Author: 小龙女
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Description: python 实现了支持向量机,简单好用(support vector machine a kind of classification algorithm, realize in python)
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Author: Silenston
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Description: 用SVM在python平台实现手写数字的识别(using the algorithm of SVM to recognition of handwritten numerals on python)
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Size: 187392 |
Author: THTing
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Description: SVM算法实例,包括具体的结果,可以在运行完后进行比较(Example of SVM algorithm)
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Author: 琥珀瞳
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Description: support vector machine using python
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Author: bipsman |
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Description: 数据挖掘常用算法
支持向量机的简单实例,使用该方法来进行数据分类(SVM code example)
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Size: 2048 |
Author: 李建军 |
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Description: 支持向量机(SVM)——分类预测,包括核函数调参,不平衡数据问题,特征降维,网格搜索,管道机制,学习曲线,混淆矩阵,AUC曲线等(Support vector machine (SVM) - classification prediction, including kernel function parameter adjustment, unbalanced data problem, feature dimensionality reduction, grid search, pipeline mechanism, learning curve, confusion matrix, AUC curve, etc)
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Size: 24576 |
Author: xning |
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