object

# `elastic_net_regression`

Elastic net regression regressor supporting continuous and mixed-feature datasets using coordinate descent with coefficient-wise L1 shrinkage plus L2 stabilization. Learns from a dataset object implementing the `regression_dataset_protocol` protocol and returns a regressor term that can be used for prediction and exported as predicate clauses.

Availability:
`logtalk_load(elastic_net_regression(loader))`
Author: Paulo Moura
Version: 1:1:0
Date: 2026-06-16
Compilation flags:
`static, context_switching_calls`
Imports:
`public` regressor_common
Uses:
format
list
numberlist
type
Remarks:
(none)
Inherited public predicates:
check_option/1 check_options/1 check_regressor/1 default_option/1 default_options/1 diagnostic/2 diagnostics/2 export_to_clauses/4 export_to_file/4 learn/2 learn/3 option/2 option/3 predict/3 print_regressor/1 regressor_options/2 valid_option/1 valid_options/1 valid_regressor/1

## Public predicates

(no local declarations; see entity ancestors if any)

## Protected predicates

(no local declarations; see entity ancestors if any)

## Private predicates

(no local declarations; see entity ancestors if any)

## Operators

(none)

See also

linear_regression, ridge_regression, lasso_regression, knn_regression, regression_tree, random_forest_regression, gradient_boosting_regression