Exemple #1
0
class learning(object)

	def __init__(self, gm, data = None):
		if not data:
			data = sample(gm)
		self.estimator = MLE(gm, data)
		self.params = self.estimator.get_parameters()

	def sample(gm):
		
		pass

	def split_and_train(gm):
		"""
		the proposed algorithm:
			- split the model into local models and global models
			- 	estimate the (chordal?) local models
			- 	estimate the global models
			- 	repeat to convergence 
		"""
		pass
Exemple #2
0
	def __init__(self, gm, data = None):
		if not data:
			data = sample(gm)
		self.estimator = MLE(gm, data)
		self.params = self.estimator.get_parameters()