matlab接口中libsvm的使用方法和可以使用的函数.doc

文档介绍：[LIBSVM资料] matlab接口中libsvm的使用方法和可以使用的函数
matlab, libsvm, 接口
在C版的libsvm中有很多函数，朋友们都认为matlab接口中也有相应的，其实不是！matlab接口中，libsvm可以使用的函数好像不多，具体在接口文件夹的README中有说明，可以使用的函数有如下几个，可以在matlab命令行直接使用（这是我的理解）：
Usage
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matlab> model = svmtrain(training_label_vector, training_instance_matrix [, 'libsvm_options']);
        -training_label_vector:
            An m by 1 vector of training labels (type must be double).
        -training_instance_matrix:
            An m by n matrix of m training instances with n features.
            It can be dense or sparse (type must be double).
        -libsvm_options:
            A string of training options in the same format as that of LIBSVM.
matlab> [predicted_label, accuracy, decision_values/prob_estimates] = svmpredict(testing_label_vector, testing_instance_matrix, model [, 'libsvm_options']);
        -testing_label_vector:
            An m by 1 vector of prediction labels. If labels of test
            data are unknown, simply use any random values. (type must be double)
        -testing_instance_matrix:
            An m by n matrix of m testing instances with n features.
            It can be dense or sparse. (type must be double)
        -model:
            The output of svmtrain.
        -libsvm_options:
            A string of testing options in the same format as that of LIBSVM.
Returned Model Structure
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