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libsvm Toolbox >> libsvm Toolbox > svmnormalize

svmnormalize

scale the input data for correct learning

Calling Sequence

[scaled_instance,scaled_parameters] = svmnormalize(instance);
[scaled_instance,scaled_parameters] = svmnormalize(instance,[meanV,stdV]);

[scaled_instance] = svmnormalize(instance,scaled_parameters);

[scaled_instance,scaled_parameters,scaled_label,scaled_label_parameters] = svmnormalize(instance,[meanV,stdV],label,[label_mean, label_std]);

Description

Scale your data. For example, scale each attribute to a mean of 0 and a standard deviation of 1.

Examples

[label,instance]=libsvmread("demos/heart_scale");
[scaled_instance,scaled_parameters] = svmnormalize(instance,[0,1]);
cc = svmtrain(label,scaled_instance);
[predicted_label]=svmtrain(label,svmnormalize(instance,scaled_parameters));

Authors

svmgridlinear libsvm Toolbox svmpartest