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是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類,以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
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The library of linear classifier
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about libsvm for string data to classification-about libsvm for string data to classification
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线性分类器的matlab源码,可以实现多累分类-Linear classifier matlab source, multi-tired classification
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经典随机梯度下降SVM,一个简单易读的线性分类器代码,执行速度快,分类准确率也不错,适用于大规模图像分类。-The classic stochastic gradient descent SVM, a linear classifier code easier to read, faster execution speed, good classification accuracy, suitable for large-scale image classification.
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Introduction
LibShortText is an open source tool for short-text classification and analysis. It can handle the classification of, for example, titles, questions, sentences, and short messages. Main features of LibShortText include
It is mo
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liblinear1.94支持向量机的分类器-liblinear SVM classifier
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Libsvm和Liblinear都是国立台湾大学的Chih-Jen Lin博士开发的,Libsvm主要是用来进行非线性svm 分类器的生成,提出有一段时间了,而Liblinear则是去年才创建的,主要是应对large-scale的data classification,因为linear分类器的训练比非线性分类器的训练计算复杂度要低很多,时间也少很多,而且在large scale data上的性能和非线性的分类器性能相当,所以Liblinear是针对大数据而生的。(Libsvm and Libli
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