scalation.modeling.neuralnet.ELM_3L1
See theELM_3L1 companion class
The ELM_3L1 companion object provides factory methods for creating three-layer (one hidden layer) extreme learning machines. Note, 'scale' is defined in Scalaing.
Attributes
Companion
class
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class Object
trait Matchable
class Any
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Create an ELM_3L1 for a combined data-response matrix.
Create an ELM_3L1 for a combined data-response matrix.
Value parameters
col
the designated response column (defaults to the last column)
f
the activation function family for layers 1->2 (input to hidden) (defaults to tanh)
fname
the feature/variable names (defaults to null)
hparam
the hyper-parameters (defaults to Regression.hp)
nz
the number of nodes in hidden layer (-1 => use default formula)
xy
the combined input/data and output/response matrix
Attributes
Create an ELM_3L1 for a data matrix and response vector.
Create an ELM_3L1 for a data matrix and response vector.
Value parameters
f
the activation function family for layers 1->2 (input to hidden) (defaults to tanh)
fname
the feature/variable names (defaults to null)
hparam
the hyper-parameters
nz
the number of nodes in hidden layer (-1 => use default formula)
x
the m-by-n input/data matrix
y
the m-dimensional output/response vector
Attributes
Set the scale flag to the given value.
Set the scale flag to the given value.
Value parameters
scale_
the new value for the scale flag
Attributes
Inherited from:
Scaling
The 'scale' flag indicated whether the data is to be rescaled/normalized
The 'scale' flag indicated whether the data is to be rescaled/normalized
Attributes
Inherited from:
Scaling