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get_recmatrix(self,
transposed=1)
Return the back-projection matrix (i.e. |
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Inherited from object :
__delattr__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__setattr__
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__init__(self,
input_dim=None,
output_dim=None,
dtype=None,
svd=False,
reduce=False,
var_rel=1e-12,
var_abs=1e-15,
var_part=None)
The number of principal components to be kept can be specified as
'output_dim' directly (e.g. |
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_execute(self,
x,
n=None)
Project the input on the first 'n' principal components. |
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_inverse(self,
y,
n=None)
Project 'y' to the input space using the first 'n' components. |
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execute(self,
x,
*args,
**kargs)
Project the input on the first 'n' principal components. |
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get_explained_variance(self)
Return the fraction of the original variance that can be
explained by self._output_dim PCA components. |
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inverse(self,
y,
*args,
**kargs)
Project 'y' to the input space using the first 'n' components. |
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__call__(self,
x,
*args,
**kargs)
Calling an instance of Node is equivalent to call
its 'execute' method. |
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_refcast(self,
x)
Helper function to cast arrays to the internal dtype. |
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copy(self,
protocol=-1)
Return a deep copy of the node. |
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is_invertible(self)
Return True if the node can be inverted, False otherwise. |
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is_trainable(self)
Return True if the node can be trained, False otherwise. |
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is_training(self)
Return True if the node is in the training phase,
False otherwise. |
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save(self,
filename,
protocol=-1)
Save a pickled serialization of the node to 'filename'. |
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set_dtype(self,
t)
Set internal structures' dtype. |
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train(self,
x,
*args,
**kwargs)
Update the internal structures according to the input data 'x'. |
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