Ejemplo n.º 1
0
    def __init__(self, arg1, arg2=None):
        if arg2 == None:
            # create model from file
            filename = arg1
            self.model = svmc.svm_load_model(filename)
        else:
            # create model from problem and parameter
            prob, param = arg1, arg2
            self.prob = prob
            if param.gamma == 0:
                param.gamma = 1.0 / prob.maxlen
            msg = svmc.svm_check_parameter(prob.prob, param.param)
            if msg:
                raise ValueError(msg)
            self.model = svmc.svm_train(prob.prob, param.param)

        #setup some classwide variables
        self.nr_class = svmc.svm_get_nr_class(self.model)
        self.svm_type = svmc.svm_get_svm_type(self.model)
        #create labels(classes)
        intarr = svmc.new_int(self.nr_class)
        svmc.svm_get_labels(self.model, intarr)
        self.labels = int_array_to_list(intarr, self.nr_class)
        svmc.delete_int(intarr)
        #check if valid probability model
        self.probability = svmc.svm_check_probability_model(self.model)
Ejemplo n.º 2
0
    def __init__(self, arg1, arg2=None):
        if arg2 == None:
            # create model from file
            filename = arg1
            self.model = svmc.svm_load_model(filename)
        else:
            # create model from problem and parameter
            prob, param = arg1, arg2
            self.prob = prob
            if param.gamma == 0:
                param.gamma = 1.0/prob.maxlen
            msg = svmc.svm_check_parameter(prob.prob, param.param)
            if msg:
                raise ValueError, msg
            self.model = svmc.svm_train(prob.prob, param.param)

        #setup some classwide variables
        self.nr_class = svmc.svm_get_nr_class(self.model)
        self.svm_type = svmc.svm_get_svm_type(self.model)
        #create labels(classes)
        intarr = svmc.new_int(self.nr_class)
        svmc.svm_get_labels(self.model, intarr)
        self.labels = int_array_to_list(intarr, self.nr_class)
        svmc.delete_int(intarr)
        #check if valid probability model
        self.probability = svmc.svm_check_probability_model(self.model)
Ejemplo n.º 3
0
def int_array(seq):
    size = len(seq)
    array = svmc.new_int(size)
    for i, item in enumerate(seq):
        svmc.int_setitem(array, i, int(item))
    return array
Ejemplo n.º 4
0
def int_array(seq):
    size = len(seq)
    array = svmc.new_int(size)
    for i, item in enumerate(seq):
        svmc.int_setitem(array, i, int(item))
    return array