def train(self):
Classifier.train(self)
self.post_probs = self.training.posterior_probablities(
self.attributes, self.klass)
self.class_freq_dist = self.training.class_freq_dist()
for klass_value in self.klass:
self.class_freq_dist.inc(klass_value) #laplacian smoothing
def train(self):
Classifier.train(self)
self.__best_decision_stump = self.best_decision_stump(self.training)
def __init__(self, training, attributes, klass):
Classifier.__init__(self, training, attributes, klass)
self.__best_decision_stump = None
def train(self):
Classifier.train(self)
self.post_probs = self.training.posterior_probablities(self.attributes, self.klass)
self.class_freq_dist = self.training.class_freq_dist()
for klass_value in self.klass:
self.class_freq_dist.inc(klass_value)#laplacian smoothing
def __init__(self, training, attributes, klass):
Classifier.__init__(self, training, attributes, klass)
self.post_probs, self.class_freq_dist = None, None
def __init__(self, training, attributes, klass):
Classifier.__init__(self, training, attributes, klass)
def train(self):
Classifier.train(self)
self.__majority_class = self.majority_class()
def __init__(self, training, attributes, klass):
Classifier.__init__(self, training, attributes, klass)
self.__majority_class = None
self.__klassCount = {}
def train(self):
Classifier.train(self)
self.__majority_class = self.majority_class()
def __init__(self, training, attributes, klass):
Classifier.__init__(self, training, attributes, klass)
self.__majority_class = None
self.__klassCount = {}
def train(self):
Classifier.train(self)
self.__best_decision_stump = self.best_decision_stump(self.training)
def __init__(self, training, attributes, klass):
Classifier.__init__(self, training, attributes, klass)
self.__best_decision_stump = None
def __init__(self, training, attributes, klass):
Classifier.__init__(self, training, attributes, klass)
self.post_probs, self.class_freq_dist = None, None
