40 lines
1.3 KiB
Plaintext
40 lines
1.3 KiB
Plaintext
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Introduction
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============
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This tool provides a simple interface to LIBSVM with instance weight support
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Installation
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============
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Please check README for the detail.
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Usage
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=====
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matlab> model = svmtrain(training_weight_vector, training_label_vector, training_instance_matrix, 'libsvm_options')
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-training_weight_vector:
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An m by 1 vector of training weights. (type must be double)
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-training_label_vector:
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An m by 1 vector of training labels. (type must be double)
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-training_instance_matrix:
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An m by n matrix of m training instances with n features. (type must be double)
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-libsvm_options:
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A string of training options in the same format as that of LIBSVM.
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Examples
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========
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Train and test on the provided data heart_scale:
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matlab> [heart_scale_label, heart_scale_inst] = libsvmread('../heart_scale');
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matlab> heart_scale_weight = load('../heart_scale.wgt');
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matlab> model = svmtrain(heart_scale_weight, heart_scale_label, heart_scale_inst, '-c 1');
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matlab> [predict_label, accuracy, dec_values] = svmpredict(heart_scale_label, heart_scale_inst, model); % test the training data
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Train and test without weights:
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matlab> model = svmtrain([], heart_scale_label, heart_scale_inst, '-c 1');
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