SVM分类器—基于SVM方法的分类器

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用SVM方法制作的分类器1 Training Click “Learning “ from Toolbar or Menu, a dialog will appears like following : You can browse and choose the training sample data file(*.trn), or write the data file’s name into the text editor directly. And write down the training result data file(*.mdl). Then click “OK” to begin training .If you want to see training result after computation ,check the “Open model when finish” CheckBox. Testing Click “Classify “ from Toolbar or Menu, a dialog will appears like following: You can browse and choose the testing sample data file (*.tst), or write the data file’s name into the text editor directly. And write down the training result data file(*.mdl),test result file (*.rsl). Then click “OK” to begin training .If you want to see testing result after computation ,check the “Open result when finish” CheckBox. File Format The input file example_file contains the training examples. The first lines may contain comments and are ignored if they start with #. Each of the following lines represents one training example and is of the following format: .=. +1 | -1 | 0 .=. integer .=. real .=. : : ... : The class label and each of the feature/value pairs are separated by a space character. Feature/value pairs MUST be ordered by increasing feature number. Features with value zero can be skipped. The +1 as class label marks a positive example, -1 a negative example respectively. A class label of 0 indicates that this example should be classified using transduction. The predictions for the examples classified by transduction are written to the file specified through the -l option. The order of the predictions is the same as in the training data. Options There are two types of options. One is for learning, such as kernel types, kernel parameters, etc; the other is for prompt information, such as show optimize information or not. Learning Options: To configure Le

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z766002435 没有办法运行。。
2015-04-27
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思与悟 很好的算法
2014-05-29
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petro066613 很好,不过LabSVM已经非常成熟了
2014-04-01
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yuyizhixialhk 不错,受益匪浅。
2014-02-24
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huhu3650 不错,可以使用
2013-12-18
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thf210729 很好的算法
2013-10-13
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xiayingping 谢谢,参考下,可惜我要的是实例
2013-09-08
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jimolincnds 非常好的资源,很实用。
2013-08-16
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lichlichlichlich 浪费我积分,先是文件出错,然后没有exe文件,调试也无法进行
2013-08-06
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louyunnn 英文不好的同学有点难理解...
2013-08-01
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