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comparison linear_regression.py @ 118:d0a1bd0378c6

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Finished draft of OneHiddenLayerNNetClassifier to debut learner.py
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Wed, 07 May 2008 15:07:56 -0400
parents 88257dfedf8c
children f6505ec32dc3
comparison
equal deleted inserted replaced
111:88257dfedf8c 118:d0a1bd0378c6
112 self._regularizer = self._L2_regularizer * t.dot(self._W,self._W) 112 self._regularizer = self._L2_regularizer * t.dot(self._W,self._W)
113 self._new_XtX = add_inplace(self._XtX,t.dot(self._extended_input.T,self._extended_input)) 113 self._new_XtX = add_inplace(self._XtX,t.dot(self._extended_input.T,self._extended_input))
114 self._new_XtY = add_inplace(self._XtY,t.dot(self._extended_input.T,self._target)) 114 self._new_XtY = add_inplace(self._XtY,t.dot(self._extended_input.T,self._target))
115 self._new_theta = t.solve_inplace(self._theta,self._XtX,self._XtY) 115 self._new_theta = t.solve_inplace(self._theta,self._XtX,self._XtY)
116 116
117 OneShotTLearner.__init__(self) 117 MinibatchUpdatesTLearner.__init__(self)
118 118
119 def allocate(self,minibatch): 119 def allocate(self,minibatch):
120 minibatch_n_inputs = minibatch["input"].shape[1] 120 minibatch_n_inputs = minibatch["input"].shape[1]
121 minibatch_n_outputs = minibatch["target"].shape[1] 121 minibatch_n_outputs = minibatch["target"].shape[1]
122 if not self._n_inputs: 122 if not self._n_inputs: