R: Secretary Bird Optimization for Continuous Optimization and Neural Network Training

# Secretary Bird Optimization for Continuous Optimization and Neural Network Training

## Documentation for package ‘SBOAtools’ version 0.1.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

apply_minmax | Apply min-max normalization using existing bounds
clip_bounds | Clip values to lower and upper bounds
denormalize_minmax | Reverse min-max normalization
forward_mlp | Forward pass for a single-hidden-layer MLP
get_benchmark | Get a built-in benchmark definition
levy_flight | Lévy flight step generator
list_benchmarks | List built-in benchmark functions
mae_vec | Mean absolute error
mape_vec | Mean absolute percentage error
mlp_mse_fitness | MSE fitness function for MLP training
normalize_minmax | Min-max normalization
plot.sboa | Plot method for SBOA objects
plot.sboa_mlp | Plot method for SBOA-MLP objects
predict.sboa_mlp | Predict method for SBOA-MLP objects
print.sboa | Print method for SBOA objects
print.sboa_mlp | Print method for SBOA-MLP objects
rmse_vec | Root mean squared error
rsq_vec | R-squared
sboa | Secretary Bird Optimization Algorithm
sboa_mlp | Train a single-hidden-layer MLP using SBOA
sigmoid | Sigmoid activation function
unpack_mlp_params | Unpack MLP parameter vector