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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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3 results for “mode-imputation”
Simple Imputation Rules for Prediction with Missing Data: Contrasting Theoretical Guarantees with Empirical Performancestat.ML

The paper compares theoretical and empirical performance of imputation methods for missing data.

problem Missing data in real-world datasets.
method Contrast of theoretical and empirical imputation methods for prediction.
result Mean-imputation is asymptotically optimal for prediction, while mode-imputation is sub-optimal.
missing dataimputationpredictionasymptotic consistencymode-imputation
2021-04-07abs ↗pdf ↗
No imputation without representationcs.LG

Imputation with missing-indicators improves machine learning performance, especially for categorical attributes.

problem Missing values in datasets can be lost through imputation, potentially reducing model performance.
method Combines missing-indicator approach with imputation strategies on real datasets.
result Missing-indicators generally increase classification performance, especially for categorical attributes.
imputationmissing-indicatorsmachine learningclassificationcategorical attributes
2022-06-28abs ↗pdf ↗