forward_mlp: Forward pass for a single-hidden-layer MLP
In SBOAtools: Secretary Bird Optimization for Continuous Optimization and Neural Network Training
forward_mlp R Documentation
Forward pass for a single-hidden-layer MLP
Description
Computes hidden-layer activations and output predictions.
Usage
forward_mlp(params, X, input_dim, hidden_dim, output_dim)
Arguments
params
Numeric parameter vector.
X
Input matrix.
input_dim
Number of input variables.
Number of hidden neurons.
output_dim
Number of output neurons.
Value
A list containing hidden activations and predictions.
SBOAtools documentation built on May 3, 2026, 9:06 a.m.
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| forward_mlp | R Documentation |
Forward pass for a single-hidden-layer MLP
Description
Computes hidden-layer activations and output predictions.
Usage
forward_mlp(params, X, input_dim, hidden_dim, output_dim)
Arguments
params |
Numeric parameter vector. |
X |
Input matrix. |
input_dim |
Number of input variables. |
|
Number of hidden neurons. | |
output_dim |
Number of output neurons. |
Value
A list containing hidden activations and predictions.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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