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
Members list
Value members
Concrete methods
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