Penelope v0.1.0 Penelope.NIF
NIF wrapper module
for blas, see http://www.netlib.org/blas/ for libsvm, see https://github.com/cjlin1/libsvm
Link to this section Summary
Functions
z = ax + y
y = ax
module initialization callback
compiles svm model parameters into a model resource
extracts svm model parameters from a model resource
predicts a class from a feature vector
predicts an ordered list of class probabilities from a feature vector
trains an svm model using libsvm
Link to this section Functions
Link to this function
blas_saxpy(a, x, y)
blas_saxpy(a :: float, x :: Penelope.ML.Vector.t, y :: Penelope.ML.Vector.t) :: Penelope.ML.Vector.t
z = ax + y
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blas_sscal(a, x)
blas_sscal(a :: float, x :: Penelope.ML.Vector.t) :: Penelope.ML.Vector.t
y = ax
module initialization callback
compiles svm model parameters into a model resource
extracts svm model parameters from a model resource
Link to this function
svm_predict_class(model, x)
svm_predict_class(model :: reference, x :: Penelope.ML.Vector.t) :: integer
predicts a class from a feature vector
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svm_predict_probability(model, x)
svm_predict_probability(model :: reference, x :: Penelope.ML.Vector.t) :: [float]
predicts an ordered list of class probabilities from a feature vector
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svm_train(x, y, params)
svm_train(x :: [Penelope.ML.Vector.t], y :: [integer], params :: map) :: reference
trains an svm model using libsvm