dianaprior/kaggle-competition-agent-skill

tabpfn-classify

Run a TabPFN classification baseline, generate the first submission, rapidly probe features, then optimize with GBT ensembles, threshold tuning, and calibration. Use after tabpfn-explore has prepared the data and CV folds.

لغة النص الأصلي: الإنجليزية

tabpfn-core

Shared identity, behavior rules, workflow principles, and project conventions for TabPFN tabular competition skills. Referenced by tabpfn-classify, tabpfn-regress, and tabpfn-explore — not invoked directly.

لغة النص الأصلي: الإنجليزية

tabpfn-explore

EDA, data profiling, adversarial validation, preprocessing checks, CV scheme setup, and API budget verification for tabular Kaggle competitions. Run at the start of every new competition before any modeling.

لغة النص الأصلي: الإنجليزية

tabpfn-regress

Run a TabPFN regression baseline, generate the first submission, then optimize with GBT ensembles and regression-specific post-processing (clipping, target transforms, rank blending). Use after tabpfn-explore has prepared the data and CV folds.

لغة النص الأصلي: الإنجليزية