-- Hoogle documentation, generated by Haddock -- See Hoogle, http://www.haskell.org/hoogle/ -- | Haskell Bindings for libsvm -- -- Haskell Bindings for libsvm @package HSvm @version 0.1.0.2.90 module Data.SVM.Raw data CSvmNode CSvmNode :: CInt -> CDouble -> CSvmNode [index] :: CSvmNode -> CInt [value] :: CSvmNode -> CDouble data CSvmProblem CSvmProblem :: CInt -> Ptr CDouble -> Ptr (Ptr CSvmNode) -> CSvmProblem [l] :: CSvmProblem -> CInt [y] :: CSvmProblem -> Ptr CDouble [x] :: CSvmProblem -> Ptr (Ptr CSvmNode) newtype CSvmType CSvmType :: CInt -> CSvmType [unCSvmType] :: CSvmType -> CInt cSvc :: CSvmType nuSvc :: CSvmType newtype CKernelType CKernelType :: CInt -> CKernelType [unCKernelType] :: CKernelType -> CInt oneClass :: CSvmType linear :: CKernelType poly :: CKernelType epsilonSvr :: CSvmType data CSvmParameter CSvmParameter :: CSvmType -> CKernelType -> CInt -> CDouble -> CDouble -> CDouble -> CDouble -> CDouble -> CInt -> Ptr CInt -> Ptr CDouble -> CDouble -> CDouble -> CInt -> CInt -> CSvmParameter [svm_type] :: CSvmParameter -> CSvmType [kernel_type] :: CSvmParameter -> CKernelType [degree] :: CSvmParameter -> CInt [gamma] :: CSvmParameter -> CDouble [coef0] :: CSvmParameter -> CDouble [cache_size] :: CSvmParameter -> CDouble [eps] :: CSvmParameter -> CDouble [c] :: CSvmParameter -> CDouble [nr_weight] :: CSvmParameter -> CInt [weight_label] :: CSvmParameter -> Ptr CInt [weight] :: CSvmParameter -> Ptr CDouble [nu] :: CSvmParameter -> CDouble [p] :: CSvmParameter -> CDouble [shrinking] :: CSvmParameter -> CInt [probability] :: CSvmParameter -> CInt nuSvr :: CSvmType rbf :: CKernelType sigmoid :: CKernelType precomputed :: CKernelType defaultCParam :: CSvmParameter data CSvmModel c_svm_train :: Ptr CSvmProblem -> Ptr CSvmParameter -> IO (Ptr CSvmModel) c_svm_cross_validation :: Ptr CSvmProblem -> Ptr CSvmParameter -> CInt -> Ptr CDouble -> IO () c_svm_predict :: Ptr CSvmModel -> Ptr CSvmNode -> CDouble c_svm_save_model :: CString -> Ptr CSvmModel -> IO CInt c_svm_load_model :: CString -> IO (Ptr CSvmModel) c_svm_check_parameter :: Ptr CSvmProblem -> Ptr CSvmParameter -> CString c_svm_destroy_model :: FinalizerPtr CSvmModel c_clone_model_support_vectors :: Ptr CSvmModel -> IO () instance GHC.Show.Show Data.SVM.Raw.CSvmParameter instance GHC.Show.Show Data.SVM.Raw.CKernelType instance Foreign.Storable.Storable Data.SVM.Raw.CKernelType instance GHC.Show.Show Data.SVM.Raw.CSvmType instance Foreign.Storable.Storable Data.SVM.Raw.CSvmType instance Foreign.Storable.Storable Data.SVM.Raw.CSvmNode instance Foreign.Storable.Storable Data.SVM.Raw.CSvmProblem instance Foreign.Storable.Storable Data.SVM.Raw.CSvmParameter module Data.SVM type Vector = IntMap Double type Problem = [(Double, Vector)] newtype Model Model :: (ForeignPtr CSvmModel) -> Model data KernelType Linear :: KernelType RBF :: Double -> KernelType [gamma] :: KernelType -> Double Sigmoid :: Double -> Double -> KernelType [gamma] :: KernelType -> Double [coef0] :: KernelType -> Double Poly :: Double -> Double -> Int -> KernelType [gamma] :: KernelType -> Double [coef0] :: KernelType -> Double [degree] :: KernelType -> Int data Algorithm CSvc :: Double -> Algorithm [c] :: Algorithm -> Double NuSvc :: Double -> Algorithm [nu] :: Algorithm -> Double NuSvr :: Double -> Double -> Algorithm [nu] :: Algorithm -> Double [c] :: Algorithm -> Double EpsilonSvr :: Double -> Double -> Algorithm [epsilon] :: Algorithm -> Double [c] :: Algorithm -> Double OneClassSvm :: Double -> Algorithm [nu] :: Algorithm -> Double data ExtraParam ExtraParam :: Double -> Int -> Int -> ExtraParam [cacheSize] :: ExtraParam -> Double [shrinking] :: ExtraParam -> Int [probability] :: ExtraParam -> Int defaultExtra :: ExtraParam mergeKernel :: KernelType -> CSvmParameter -> CSvmParameter mergeAlgo :: Algorithm -> CSvmParameter -> CSvmParameter mergeExtra :: ExtraParam -> CSvmParameter -> CSvmParameter newCSvmNodeArray :: Vector -> IO (Ptr CSvmNode) newCSvmProblem :: Problem -> IO (Ptr CSvmProblem) freeCSVmProblem :: Ptr CSvmProblem -> IO () withProblem :: Problem -> (Ptr CSvmProblem -> IO a) -> IO a withParam :: ExtraParam -> Algorithm -> KernelType -> (Ptr CSvmParameter -> IO a) -> IO a checkParam :: Ptr CSvmProblem -> Ptr CSvmParameter -> IO () train' :: ExtraParam -> Algorithm -> KernelType -> Problem -> IO (Model) -- | The train function allows training a Model starting from -- a Problem by specifying an Algorithm and a -- KernelType train :: Algorithm -> KernelType -> Problem -> IO (Model) crossValidate' :: ExtraParam -> Algorithm -> KernelType -> Problem -> Int -> IO [Double] crossValidate :: Algorithm -> KernelType -> Problem -> Int -> IO [Double] saveModel :: Model -> FilePath -> IO () loadModel :: FilePath -> IO (Model) predict :: Model -> Vector -> Double