package libsvm

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libsvm
- README
- Library libsvm
  - Libsvm
    
    Svm
    
    Problem
    
    Model
    
    Stats
- Sources
  - libsvm
    
    libsvm.ml

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Module `Libsvm.Stats`Source

These functions compute several performance measures to compare the predicted values of a SVM model to the expected values of a given test data set. For more details, have a look on page 8 in the LIBSVM paper

Sourceval calc_n_correct : Lacaml.D.vec -> Lacaml.D.vec -> int

calc_n_correct expected predicted

returns
the number of correctly predicted labels.

raises Invalid_argument
if the vector dimensions do not match.

Sourceval calc_accuracy : Lacaml.D.vec -> Lacaml.D.vec -> float

calc_accuracy expected predicted

returns
the ratio (in percent) of correctly predicted labels to the number of all labels.

raises Invalid_argument
if the vector dimensions do not match.

Sourceval calc_mse : Lacaml.D.vec -> Lacaml.D.vec -> float

calc_mse expected predicted

returns
the mean sum of squared errors.

raises Invalid_argument
if the vector dimensions do not match.

Sourceval calc_scc : Lacaml.D.vec -> Lacaml.D.vec -> float

calc_scc expected predicted

returns
the squared correlation coefficient.

raises Invalid_argument
if the vector dimensions do not match.

package libsvm

Module Libsvm.StatsSource

Module `Libsvm.Stats`Source