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September 10, 2025International Journal of Emerging Multidiciplinaries Biomedical and Clinical Research

Modified Adaptive Lasso for Classification of High Dimensional Data

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Authors

ELEmmanuel Lekwot TDTukur DahiruAhmadu Bello University HDH. G. DikkoAhmadu Bello University

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Implication

This study demonstrates that modified adaptive lasso enhances predictive accuracy in high-dimensional gene expression datasets, indicating its potential for medical diagnostics.

Key Points

MALASSO achieved 98.45% accuracy for leukemia, significantly improving classification outcomes.
The new weighting mechanism reduces selection bias associated with traditional LASSO methods, allowing for better variable selection.
Extensive simulations and real-world applications demonstrate MALASSO's superior performance compared to Adaptive LASSO and Elastic Net.
This approach paves the way for advancements in high-dimensional medical diagnostics and efficient biomarker discovery.

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Lekwot et al. (2025) studied this question.

synapsesocial.com/papers/68c1ae6654b1d3bfb60e627e https://doi.org/10.54938/ijemdbmcr.2025.03.1.411

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Implication

This study demonstrates that modified adaptive lasso enhances predictive accuracy in high-dimensional gene expression datasets, indicating its potential for medical diagnostics.

Modified Adaptive Lasso for Classification of High Dimensional Data

Discussion

Member takes

Implication

Key Points

Cite This Study

Modified Adaptive Lasso for Classification of High Dimensional Data

Discussion

Member takes

Implication

Key Points

Cite This Study

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