MAPLE: Mapper Based Localized Prediction with Data Driven Cover Selection for High dimensional Data
MAPLE：基于 Mapper 的局部预测与数据驱动覆盖选择
High dimensional biomedical data often exhibit nonlinear, heterogeneous, and manifold driven structures that challenge global parametric and tree-based models. We propose MAPLE (mapper-based Adaptive Prediction via Local Estimation), a localized prediction framework grounded in topological data analysis. The method is formulated as a nonparametric estimator of conditional class probabilities that adapts to the intrinsic geometry of the predictor space. Neighborhoods are…