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Imputing Missing Observations with Time Sliced Synthetic Minority
Oversampling Technique

Imputing Missing Observations with Time Sliced Synthetic Minority Oversampling Technique

14 January 2022

Andrew Baumgartner

ArXiv (abs)PDF HTML

Papers citing "Imputing Missing Observations with Time Sliced Synthetic Minority Oversampling Technique"

2 / 2 papers shown

Setting the Standard: Recommended Practices for Data Preprocessing in Data-Driven Climate Prediction

Setting the Standard: Recommended Practices for Data Preprocessing in Data-Driven Climate Prediction

Jason C. Furtado

Maria J. Molina

Marybeth C. Arcodia

Weston Anderson

...

Jhayron S. Pérez-Carrasquilla

Maike Sonnewald

Brian G. Zimmerman

132

0

0

09 Aug 2025

Transforming Credit Risk Analysis: A Time-Series-Driven ResE-BiLSTM Framework for Post-Loan Default Detection

Transforming Credit Risk Analysis: A Time-Series-Driven ResE-BiLSTM Framework for Post-Loan Default Detection

Chang Chuan Goh

Tangtangfang Fang

Anthony Graham Bellotti

131

0

0

01 Aug 2025