John T. Hancock

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 40

Top Topics

Highly Imbalanced

Fraud Detection

Decision Tree Algorithm

Top Venues

Publications

Huanjing Wang, Qianxin Liang, John T. Hancock, Taghi M. Khoshgoftaar
Feature selection strategies: a comparative analysis of SHAP-value and importance-based methods. J. Big Data 11 (1) (2024)
John T. Hancock, Huanjing Wang, Taghi M. Khoshgoftaar, Qianxin Liang
Data reduction techniques for highly imbalanced medicare Big Data. J. Big Data 11 (1) (2024)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Azadeh Abdollah Zadeh
One-Class Classifier Performance: Comparing Majority versus Minority Class Training. ICTAI (2023)
Huanjing Wang, Qianxin Liang, John T. Hancock, Taghi M. Khoshgoftaar
Enhancing Credit Card Fraud Detection Through a Novel Ensemble Feature Selection Technique. IRI (2023)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Azadeh Abdollah Zadeh
Investigating the effectiveness of one-class and binary classification for fraud detection. J. Big Data 10 (1) (2023)
John T. Hancock, Richard A. Bauder, Huanjing Wang, Taghi M. Khoshgoftaar
Explainable machine learning models for Medicare fraud detection. J. Big Data 10 (1) (2023)
Joffrey L. Leevy, Justin M. Johnson, John T. Hancock, Taghi M. Khoshgoftaar
Threshold optimization and random undersampling for imbalanced credit card data. J. Big Data 10 (1) (2023)
John T. Hancock, Taghi M. Khoshgoftaar
Exploring Maximum Tree Depth and Random Undersampling in Ensemble Trees to Optimize the Classification of Imbalanced Big Data. SN Comput. Sci. 4 (5) (2023)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar
Assessing One-Class and Binary Classification Approaches for Identifying Medicare Fraud. IRI (2023)
John T. Hancock, Taghi M. Khoshgoftaar
Data Reduction to Improve the Performance of One-Class Classifiers on Highly Imbalanced Big Data. ICMLA (2023)
John T. Hancock, Richard A. Bauder, Taghi M. Khoshgoftaar
A Model-Agnostic Feature Selection Technique to Improve the Performance of One-Class Classifiers. ICTAI (2023)
Huanjing Wang, John T. Hancock, Taghi M. Khoshgoftaar
Improving Medicare Fraud Detection through Big Data Size Reduction Techniques. SOSE (2023)
John T. Hancock, Taghi M. Khoshgoftaar, Justin M. Johnson
Evaluating classifier performance with highly imbalanced Big Data. J. Big Data 10 (1) (2023)
Huanjing Wang, Qianxin Liang, John T. Hancock, Taghi M. Khoshgoftaar
A Comparative Study of Model-Agnostic and Importance-Based Feature Selection Approaches. CogMI (2023)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar
Comparative analysis of binary and one-class classification techniques for credit card fraud data. J. Big Data 10 (1) (2023)
John T. Hancock, Taghi M. Khoshgoftaar
Hyperparameter Tuning for Medicare Fraud Detection in Big Data. SN Comput. Sci. 3 (6) (2022)
Joffrey L. Leevy, Taghi M. Khoshgoftaar, John T. Hancock
Evaluating Performance Metrics for Credit Card Fraud Classification. ICTAI (2022)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Jared M. Peterson
IoT information theft prediction using ensemble feature selection. J. Big Data 9 (1) (2022)
John T. Hancock, Taghi M. Khoshgoftaar
Optimizing Ensemble Trees for Big Data Healthcare Fraud Detection. IRI (2022)
John T. Hancock, Justin M. Johnson, Taghi M. Khoshgoftaar
A Comparative Approach to Threshold Optimization for Classifying Imbalanced Data. CIC (2022)
John T. Hancock, Taghi M. Khoshgoftaar, Justin M. Johnson
The Effects of Random Undersampling for Big Data Medicare Fraud Detection. SOSE (2022)
Richard Zuech, John T. Hancock, Taghi M. Khoshgoftaar
A new feature popularity framework for detecting cyberattacks using popular features. J. Big Data 9 (1) (2022)
John T. Hancock, Taghi M. Khoshgoftaar, Justin M. Johnson
Informative Evaluation Metrics for Highly Imbalanced Big Data Classification. ICMLA (2022)
Richard Zuech, John T. Hancock, Taghi M. Khoshgoftaar
Detecting Web Attacks in Severely Imbalanced Network Traffic Data. IRI (2021)
John T. Hancock, Taghi M. Khoshgoftaar, Joffrey L. Leevy
Detecting SSH and FTP Brute Force Attacks in Big Data. ICMLA (2021)
Richard Zuech, John T. Hancock, Taghi M. Khoshgoftaar
Feature Popularity Between Different Web Attacks with Supervised Feature Selection Rankers. ICMLA (2021)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Jared M. Peterson
Detecting Information Theft Attacks in the Bot-IoT Dataset. ICMLA (2021)
John T. Hancock, Taghi M. Khoshgoftaar
Impact of Hyperparameter Tuning in Classifying Highly Imbalanced Big Data. IRI (2021)
John T. Hancock, Taghi M. Khoshgoftaar
Gradient Boosted Decision Tree Algorithms for Medicare Fraud Detection. SN Comput. Sci. 2 (4) (2021)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Jared M. Peterson
An Easy-to-Classify Approach for the Bot-IoT Dataset. CogMI (2021)
John T. Hancock, Taghi M. Khoshgoftaar
Leveraging LightGBM for Categorical Big Data. BigDataService (2021)
Richard Zuech, John T. Hancock, Taghi M. Khoshgoftaar
Detecting web attacks using random undersampling and ensemble learners. J. Big Data 8 (1) (2021)
Joffrey L. Leevy, John T. Hancock, Richard Zuech, Taghi M. Khoshgoftaar
Detecting cybersecurity attacks across different network features and learners. J. Big Data 8 (1) (2021)
Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Naeem Seliya
IoT Reconnaissance Attack Classification with Random Undersampling and Ensemble Feature Selection. CIC (2021)
Richard Zuech, John T. Hancock, Taghi M. Khoshgoftaar
Detecting SQL Injection Web Attacks Using Ensemble Learners and Data Sampling. CSR (2021)
John T. Hancock, Taghi M. Khoshgoftaar
Medicare Fraud Detection using CatBoost. IRI (2020)
John T. Hancock, Taghi M. Khoshgoftaar
Survey on categorical data for neural networks. J. Big Data 7 (1) (2020)
John T. Hancock, Taghi M. Khoshgoftaar
CatBoost for big data: an interdisciplinary review. J. Big Data 7 (1) (2020)
Joffrey L. Leevy, John T. Hancock, Richard Zuech, Taghi M. Khoshgoftaar
Detecting Cybersecurity Attacks Using Different Network Features with LightGBM and XGBoost Learners. CogMI (2020)
John T. Hancock, Taghi M. Khoshgoftaar
Performance of CatBoost and XGBoost in Medicare Fraud Detection. ICMLA (2020)