package libsvm
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Library
Module
Module type
Parameter
Class
Class type
Source
Module Svm.ProblemSource
Type of a SVM problem (training set).
create ~x ~y constructs a problem from a sparse encoding x of training vectors and a target vector y.
create_dense ~x ~y constructs a problem from a dense encoding x of training vectors and a target vector y. This is useful in particular in conjunction with the `PRECOMPUTED type of kernel when invoking train. In that case x represents a kernel matrix of the following form:
1 K(x1,x1) K(x1,x2) ... K(x1,xL)
2 K(x2,x1) K(x2,x2) ... K(x2,xL)
...
L K(xL,x1) K(xL,x2) ... K(xL,xL)
where L denotes the number of training instances and K(x,y) is the precomputed kernel value of the two training instances x and y.
get_targets prob
output prob oc outputs the problem prob to an output channel oc. NOTE: the function does not close the output channel.
min_max_feats prob
scale ?lower ?upper prob scales in place prob such that each feature (attribute) lies in the range [lower,upper]. The default range is [-1,1].