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#
#
# Nim's Runtime Library
# (c) Copyright 2012 Andreas Rumpf
#
# See the file "copying.txt", included in this
# distribution, for details about the copyright.
#
## This module is a low level wrapper for `libsvm`:idx:.
{.deadCodeElim: on.}
const
LIBSVM_VERSION* = 312
when defined(windows):
const svmdll* = "libsvm.dll"
elif defined(macosx):
const svmdll* = "libsvm.dylib"
else:
const svmdll* = "libsvm.so"
type
Node*{.pure, final.} = object
index*: cint
value*: cdouble
Problem*{.pure, final.} = object
L*: cint
y*: ptr cdouble
x*: ptr ptr Node
Type*{.size: sizeof(cint).} = enum
C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR
KernelType*{.size: sizeof(cint).} = enum
LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED
Parameter*{.pure, final.} = object
typ*: Type
kernelType*: KernelType
degree*: cint # for poly
gamma*: cdouble # for poly/rbf/sigmoid
coef0*: cdouble # for poly/sigmoid
# these are for training only
cache_size*: cdouble # in MB
eps*: cdouble # stopping criteria
C*: cdouble # for C_SVC, EPSILON_SVR and NU_SVR
nr_weight*: cint # for C_SVC
weight_label*: ptr cint # for C_SVC
weight*: ptr cdouble # for C_SVC
nu*: cdouble # for NU_SVC, ONE_CLASS, and NU_SVR
p*: cdouble # for EPSILON_SVR
shrinking*: cint # use the shrinking heuristics
probability*: cint # do probability estimates
{.deprecated: [Tnode: Node, Tproblem: Problem, Ttype: Type,
TKernelType: KernelType, Tparameter: Parameter].}
#
# svm_model
#
type
Model*{.pure, final.} = object
param*: Parameter # parameter
nr_class*: cint # number of classes, = 2 in regression/one class svm
L*: cint # total #SV
SV*: ptr ptr Node # SVs (SV[l])
sv_coef*: ptr ptr cdouble # coefficients for SVs in decision functions (sv_coef[k-1][l])
rho*: ptr cdouble # constants in decision functions (rho[k*(k-1)/2])
probA*: ptr cdouble # pariwise probability information
probB*: ptr cdouble # for classification only
label*: ptr cint # label of each class (label[k])
nSV*: ptr cint # number of SVs for each class (nSV[k])
# nSV[0] + nSV[1] + ... + nSV[k-1] = l
# XXX
free_sv*: cint # 1 if svm_model is created by svm_load_model
# 0 if svm_model is created by svm_train
{.deprecated: [TModel: Model].}
proc train*(prob: ptr Problem, param: ptr Parameter): ptr Model{.cdecl,
importc: "svm_train", dynlib: svmdll.}
proc cross_validation*(prob: ptr Problem, param: ptr Parameter, nr_fold: cint,
target: ptr cdouble){.cdecl,
importc: "svm_cross_validation", dynlib: svmdll.}
proc save_model*(model_file_name: cstring, model: ptr Model): cint{.cdecl,
importc: "svm_save_model", dynlib: svmdll.}
proc load_model*(model_file_name: cstring): ptr Model{.cdecl,
importc: "svm_load_model", dynlib: svmdll.}
proc get_svm_type*(model: ptr Model): cint{.cdecl, importc: "svm_get_svm_type",
dynlib: svmdll.}
proc get_nr_class*(model: ptr Model): cint{.cdecl, importc: "svm_get_nr_class",
dynlib: svmdll.}
proc get_labels*(model: ptr Model, label: ptr cint){.cdecl,
importc: "svm_get_labels", dynlib: svmdll.}
proc get_svr_probability*(model: ptr Model): cdouble{.cdecl,
importc: "svm_get_svr_probability", dynlib: svmdll.}
proc predict_values*(model: ptr Model, x: ptr Node, dec_values: ptr cdouble): cdouble{.
cdecl, importc: "svm_predict_values", dynlib: svmdll.}
proc predict*(model: ptr Model, x: ptr Node): cdouble{.cdecl,
importc: "svm_predict", dynlib: svmdll.}
proc predict_probability*(model: ptr Model, x: ptr Node,
prob_estimates: ptr cdouble): cdouble{.cdecl,
importc: "svm_predict_probability", dynlib: svmdll.}
proc free_model_content*(model_ptr: ptr Model){.cdecl,
importc: "svm_free_model_content", dynlib: svmdll.}
proc free_and_destroy_model*(model_ptr_ptr: ptr ptr Model){.cdecl,
importc: "svm_free_and_destroy_model", dynlib: svmdll.}
proc destroy_param*(param: ptr Parameter){.cdecl, importc: "svm_destroy_param",
dynlib: svmdll.}
proc check_parameter*(prob: ptr Problem, param: ptr Parameter): cstring{.
cdecl, importc: "svm_check_parameter", dynlib: svmdll.}
proc check_probability_model*(model: ptr Model): cint{.cdecl,
importc: "svm_check_probability_model", dynlib: svmdll.}
proc set_print_string_function*(print_func: proc (arg: cstring) {.cdecl.}){.
cdecl, importc: "svm_set_print_string_function", dynlib: svmdll.}
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