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March 13, 2026PLoS ONEOpen Access

Correction: A two-stage forecasting model using random forest subset-based feature selection and BiGRU with attention mechanism: Application to stock indices

Shafiqah Azman Dharini Pathmanathan Vimala Balakrishnan

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Key Points

The central aim is to provide a correction regarding a two-stage forecasting model for stock indices.
Utilized a two-stage forecasting model.
Implemented random forest for feature selection.
Employed BiGRU with an attention mechanism for predictions.
Provided corrections to previously published findings.
Clarified the performance enhancements of the forecasting model.

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Implication

Correction reports on a two-stage forecasting model for stock indices using advanced machine learning techniques, highlighting enhancements.

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Cite This Study

Azman et al. (2026) studied this question.

synapsesocial.com/papers/69b79df38166e15b153ab1db https://doi.org/10.1371/journal.pone.0345034

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