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August 25, 2025Deleted JournalOpen Access

Optimizing multivariate adaptive regression splines (MARS) with coordinate descent to accurately select the best model for house price prediction

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The CD-MARS model shows lower mean squared error compared to traditional MARS, enhancing predictive accuracy.
With a coefficient of determination of 0.931, CD-MARS significantly outperforms traditional MARS with 0.8952.
The study utilized a dataset of house prices to effectively evaluate the model's performance metrics.
Integrating coordinate descent into model selection helps to manage over-fitting, boosting model reliability.

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This method finds the best model for house prices, improving accuracy by reducing over-fitting using coordinate descent.

Adonia et al. (2025) studied this question.

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