Enhancing Cross-Platform Correlations in GAM with Varying PC Counts

Jan 19, 2026

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This study focuses on improving cross-platform correlations in Generalized Additive Models (GAM) by examining the effects of varying the number of Principal Components (PCs). We analyze how different PC counts influence correlation measures, particularly the Pearson correlation coefficient (r). By optimizing the PC selection process, we aim to enhance model accuracy and predictive power across diverse datasets. The findings contribute valuable insights for researchers looking to refine their analytical approaches in GAM and related fields.

lesley-crawford

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Enhancing Cross-Platform Correlations in GAM with Varying PC Counts

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