# Path: pattern/vector/svm/libsvm.py
# C_SVC = 0
# NU_SVC = 1
# ONE_CLASS = 2
# EPSILON_SVR = 3
# NU_SVR = 4
# LINEAR = 0
# POLY = 1
# RBF = 2
# SIGMOID = 3
# PRECOMPUTED = 4
# PRINT_STRING_FUN = CFUNCTYPE(None, c_char_p)
# def print_null(s):
# def genFields(names, types):
# def fillprototype(f, restype, argtypes):
# 	def __str__(self):
# def gen_svm_nodearray(xi, feature_max=None, isKernel=None):
# 	def __init__(self, y, x, isKernel=None):
# 	def __init__(self, options = None):
# 	def __str__(self):
# 	def set_to_default_values(self):
# 	def parse_options(self, options):
# 	def __init__(self):
# 	def __del__(self):
# 	def get_svm_type(self):
# 	def get_nr_class(self):
# 	def get_svr_probability(self):
# 	def get_labels(self):
# 	def get_sv_indices(self):
# 	def get_nr_sv(self):
# 	def is_probability_model(self):
# 	def get_sv_coef(self):
# 	def get_SV(self):
# def toPyModel(model_ptr):
# class svm_node(Structure):
# class svm_problem(Structure):
# class svm_parameter(Structure):
# class svm_model(Structure):


from builtins import str, bytes, dict, int
from builtins import object, range
from builtins import map, zip, filter
from .libsvm import *
from .libsvm import __all__ as svm_all
import os
import sys
#!/usr/bin/env python

from __future__ import absolute_import
from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division



__all__ = ['evaluations', 'svm_load_model', 'svm_predict', 'svm_read_problem',

# Path: pattern/vector/svm/libsvm.py
# C_SVC = 0
# NU_SVC = 1
# ONE_CLASS = 2
# EPSILON_SVR = 3
# NU_SVR = 4
# LINEAR = 0
# POLY = 1
# RBF = 2
# SIGMOID = 3
# PRECOMPUTED = 4
# PRINT_STRING_FUN = CFUNCTYPE(None, c_char_p)
# def print_null(s):
# def genFields(names, types):
# def fillprototype(f, restype, argtypes):
# 	def __str__(self):
# def gen_svm_nodearray(xi, feature_max=None, isKernel=None):
# 	def __init__(self, y, x, isKernel=None):
# 	def __init__(self, options = None):
# 	def __str__(self):
# 	def set_to_default_values(self):
# 	def parse_options(self, options):
# 	def __init__(self):
# 	def __del__(self):
# 	def get_svm_type(self):
# 	def get_nr_class(self):
# 	def get_svr_probability(self):
# 	def get_labels(self):
# 	def get_sv_indices(self):
# 	def get_nr_sv(self):
# 	def is_probability_model(self):
# 	def get_sv_coef(self):
# 	def get_SV(self):
# def toPyModel(model_ptr):
# class svm_node(Structure):
# class svm_problem(Structure):
# class svm_parameter(Structure):
# class svm_model(Structure):


# Path: pattern/vector/svm/libsvmutil.py
from builtins import str, bytes, dict, int
from builtins import object, range
from builtins import map, zip, filter
from .libsvm import *
from .libsvm import __all__ as svm_all
import os
import sys

#!/usr/bin/env python

from __future__ import absolute_import
from __future__ import unicode_literals
from __future__ import print_function
from __future__ import division



__all__ = ['evaluations', 'svm_load_model', 'svm_predict', 'svm_read_problem',

           'svm_save_model', 'svm_train'] + svm_all