Richard A. Bauder

According to our database, Richard A. Bauder authored at least 27 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Explainable machine learning models for Medicare fraud detection.

John T. Hancock, Richard A. Bauder, Huanjing Wang, Taghi M. Khoshgoftaar

J. Big Data, December, 2023

A Model-Agnostic Feature Selection Technique to Improve the Performance of One-Class Classifiers.

John T. Hancock, Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 35th IEEE International Conference on Tools with Artificial Intelligence, 2023

2020

Investigating the relationship between time and predictive model maintenance.

Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, Naeem Seliya

J. Big Data, 2020

Investigating class rarity in big data.

Tawfiq Hasanin, Taghi M. Khoshgoftaar, Joffrey L. Leevy, Richard A. Bauder

J. Big Data, 2020

A study on rare fraud predictions with big Medicare claims fraud data.

Richard A. Bauder, Taghi M. Khoshgoftaar

Intell. Data Anal., 2020

2019

The effects of class rarity on the evaluation of supervised healthcare fraud detection models.

Matthew Herland, Richard A. Bauder, Taghi M. Khoshgoftaar

J. Big Data, 2019

Severely imbalanced Big Data challenges: investigating data sampling approaches.

Tawfiq Hasanin, Taghi M. Khoshgoftaar, Joffrey L. Leevy, Richard A. Bauder

J. Big Data, 2019

Evaluating Model Predictive Performance: A Medicare Fraud Detection Case Study.

Richard A. Bauder, Matthew Herland, Taghi M. Khoshgoftaar

Proceedings of the 20th IEEE International Conference on Information Reuse and Integration for Data Science, 2019

The Effect of Time on the Maintenance of a Predictive Model.

Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, Naeem Seliya

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

2018

Machine Learning Algorithms with Big Medicare Fraud Data.

Richard A. Bauder

PhD thesis, 2018

A survey on addressing high-class imbalance in big data.

Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, Naeem Seliya

J. Big Data, 2018

Big Data fraud detection using multiple medicare data sources.

Matthew Herland, Taghi M. Khoshgoftaar, Richard A. Bauder

J. Big Data, 2018

The effects of varying class distribution on learner behavior for medicare fraud detection with imbalanced big data.

Richard A. Bauder, Taghi M. Khoshgoftaar

Health Inf. Sci. Syst., 2018

Identifying Medicare Provider Fraud with Unsupervised Machine Learning.

Richard A. Bauder, Raquel da Rosa, Taghi M. Khoshgoftaar

Proceedings of the 2018 IEEE International Conference on Information Reuse and Integration, 2018

Medicare Fraud Detection Using Random Forest with Class Imbalanced Big Data.

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 2018 IEEE International Conference on Information Reuse and Integration, 2018

A Survey of Medicare Data Processing and Integration for Fraud Detection.

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 2018 IEEE International Conference on Information Reuse and Integration, 2018

Data Sampling Approaches with Severely Imbalanced Big Data for Medicare Fraud Detection.

Richard A. Bauder, Taghi M. Khoshgoftaar, Tawfiq Hasanin

Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018

An Empirical Study on Class Rarity in Big Data.

Richard A. Bauder, Taghi M. Khoshgoftaar, Tawfiq Hasanin

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Fraud Detection with a Limited Number of Known Fraudulent Medicare Providers.

Richard A. Bauder, Taghi M. Khoshgoftaar, Amri Napolitano

Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

The Detection of Medicare Fraud Using Machine Learning Methods with Excluded Provider Labels.

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

2017

Medical Provider Specialty Predictions for the Detection of Anomalous Medicare Insurance Claims.

Matthew Herland, Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 2017 IEEE International Conference on Information Reuse and Integration, 2017

Estimating Outlier Score Probabilities.

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 2017 IEEE International Conference on Information Reuse and Integration, 2017

Medicare Fraud Detection Using Machine Learning Methods.

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

Multivariate Anomaly Detection in Medicare using Model Residuals and Probabilistic Programming.

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

2016

A Novel Method for Fraudulent Medicare Claims Detection from Expected Payment Deviations (Application Paper).

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 17th IEEE International Conference on Information Reuse and Integration, 2016

Predicting Medical Provider Specialties to Detect Anomalous Insurance Claims.

Richard A. Bauder, Taghi M. Khoshgoftaar, Aaron N. Richter, Matthew Herland

Proceedings of the 28th IEEE International Conference on Tools with Artificial Intelligence, 2016

A Probabilistic Programming Approach for Outlier Detection in Healthcare Claims.

Richard A. Bauder, Taghi M. Khoshgoftaar

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016