HI-PMK is a data-dependent kernel for incomplete heterogeneous tabular data that treats missing values as a separate mass bucket and maximizes uncertainty, reporting improved classification and clustering over baselines.
Huber and Elvezio M
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HI-PMK: A Data-Dependent Kernel for Incomplete Heterogeneous Data Representation
HI-PMK is a data-dependent kernel for incomplete heterogeneous tabular data that treats missing values as a separate mass bucket and maximizes uncertainty, reporting improved classification and clustering over baselines.