def learn(self, data):
print("Learning")
if self.model is None:
self.model = RootNode(learn(data))
else:
augment_spn(self.model.children[0], data,
self.model.children[0].scope)
#self.model.evaluate(data, mpe=False)
#self.model.hard_em(data)
print(np.mean(self.model.evaluate(data, mpe=False)))
class LearnSPN:
def __init__(self):
self.model = None
def learn(self, data):
self.model = RootNode(learn(data))
def evaluate(self, obs, mpe=False):
assert self.model, "You gotta run learn on some data at least once!!"
return self.model.evaluate(obs, mpe=mpe)
class IncrementalLearnSPN(LearnSPN):
def __init__(self):
super(IncrementalLearnSPN, self).__init__()
def learn(self, data):
print("Learning")
if self.model is None:
self.model = RootNode(learn(data))
else:
augment_spn(self.model.children[0], data,
self.model.children[0].scope)
#self.model.evaluate(data, mpe=False)
#self.model.hard_em(data)
print(np.mean(self.model.evaluate(data, mpe=False)))
def learn(self, data):
self.model = RootNode(learn(data))