| 2025 | FlAIRS | Choosing the Right Metrics: A Study of Performance Measurement for Binary Classification in Imbalanced and Big Data. | Mary Anne Walauskis, Taghi M. Khoshgoftaar |
| 2025 | ICMLA | Medical Imaging with Deep Learning: A Comparison of CNN and Transformer Models. | Kehan Gao, Sarah Tasneem, Taghi M. Khoshgoftaar |
| 2025 | ICMLA | Applying Machine Learning to Classify Automobile Repossession Success. | Preston Billion-Polak, Andy Sinclair, Taghi M. Khoshgoftaar |
| 2025 | ICMLA | Unsupervised Feature Extraction using Convolutional Autoencoder for Credit Card Fraud Detection. | Zahra Salekshahrezaee, Mary Anne Walauskis, Taghi M. Khoshgoftaar |
| 2025 | ICMLA | Return-to-Work Classification of Occupational Injury Claims via Rank-Ordering. | Gonzalo A. Vivian, Chelsea M. Zuvieta, Taghi M. Khoshgoftaar |
| 2025 | IRI | A New and Effective Technique for Unsupervised Labeling and Feature Selection with Applications in Healthcare Fraud Detection. | John T. Hancock, Robert K. L. Kennedy, Mary Anne Walauskis, Taghi M. Khoshgoftaar |
| 2025 | IRI | The Impact of Class Imbalance on Unsupervised Deep Anomaly Detection for Cognitive Data. | Zahra Salekshahrezaee, Taghi M. Khoshgoftaar |
| 2025 | IRI | Unsupervised Cognitive Impairment Detection Using Convolutional Autoencoders and Isolation Forest. | Zahra Salekshahrezaee, Taghi M. Khoshgoftaar |
| 2025 | ICTAI | Examining the Impact of Feature Selection for Contrastive Learning in Fraud Detection. | Preston Billion-Polak, Taghi M. Khoshgoftaar |
| 2025 | ICTAI | A Novel Technique to Rank-Order Occupational Injury Claims for Return-to-Work Prediction. | Gonzalo A. Vivian, Chelsea M. Zuvieta, Taghi M. Khoshgoftaar |
| 2024 | ICMLA | An Evaluation of Low-Shot Learning Techniques for the Detection of Credit Card Fraud. | Preston Billion-Polak, Taghi M. Khoshgoftaar |
| 2024 | ICMLA | New Class Labeling and Evaluation Methodology for Balanced and Highly Imbalanced Data. | Mary Anne Walauskis, Taghi M. Khoshgoftaar |
| 2024 | ICTAI | Enhancing Medicare Fraud Detection: Random Undersampling Followed by SHAP-Driven Feature Selection with Big Data. | Qianxin Liang, Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2024 | ICTAI | A Comparison of Low-Shot Learning Methods for Imbalanced Binary Classification. | Preston Billion-Polak, Taghi M. Khoshgoftaar |
| 2024 | ICTAI | Confident Labels: A Novel Approach to New Class Labeling and Evaluation on Highly Imbalanced Data. | Mary Anne Walauskis, Taghi M. Khoshgoftaar |
| 2023 | ICMLA | Data Reduction to Improve the Performance of One-Class Classifiers on Highly Imbalanced Big Data. | John T. Hancock, Taghi M. Khoshgoftaar |
| 2023 | IRI | Unsupervised Anomaly Detection of Class Imbalanced Cognition Data Using an Iterative Cleaning Method. | Robert K. L. Kennedy, Zahra Salekshahrezaee, Taghi M. Khoshgoftaar |
| 2023 | IRI | Assessing One-Class and Binary Classification Approaches for Identifying Medicare Fraud. | Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar |
| 2023 | IRI | Enhancing Credit Card Fraud Detection Through a Novel Ensemble Feature Selection Technique. | Huanjing Wang, Qianxin Liang, John T. Hancock, Taghi M. Khoshgoftaar |
| 2023 | ICTAI | A Model-Agnostic Feature Selection Technique to Improve the Performance of One-Class Classifiers. | John T. Hancock, Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2023 | ICTAI | One-Class Classifier Performance: Comparing Majority versus Minority Class Training. | Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Azadeh Abdollah Zadeh |
| 2022 | FlAIRS | A Comparison of House Price Classification with Structured and Unstructured Text Data. | Erika Cardenas, Connor Shorten, Taghi M. Khoshgoftaar, Borivoje Furht |
| 2022 | FlAIRS | An Exploration of Consistency Learning with Data Augmentation. | Connor Shorten, Taghi M. Khoshgoftaar |
| 2022 | FlAIRS | Predicting the Severity of COVID-19 Respiratory Illness with Deep Learning. | Connor Shorten, Taghi M. Khoshgoftaar, Javad Hashemi, Safiya George Dalmida, David Newman, Debarshi Datta, Laurie Martinez, Candice Sareli, Paula Eckard |
| 2022 | ICMLA | Informative Evaluation Metrics for Highly Imbalanced Big Data Classification. | John T. Hancock, Taghi M. Khoshgoftaar, Justin M. Johnson |
| 2022 | ICMLA | Cost-Sensitive Ensemble Learning for Highly Imbalanced Classification. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2022 | IRI | Optimizing Ensemble Trees for Big Data Healthcare Fraud Detection. | John T. Hancock, Taghi M. Khoshgoftaar |
| 2022 | IRI | Healthcare Provider Summary Data for Fraud Classification. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2022 | IRI | A Class-Imbalanced Study with Feature Extraction via PCA and Convolutional Autoencoder. | Zahra Salekshahrezaee, Joffrey L. Leevy, Taghi M. Khoshgoftaar |
| 2022 | ICTAI | Evaluating Performance Metrics for Credit Card Fraud Classification. | Joffrey L. Leevy, Taghi M. Khoshgoftaar, John T. Hancock |
| 2022 | ICTAI | GANs for Class-Imbalanced Data: A Meta-Analysis of GitHub Projects. | Rick Sauber-Cole, Taghi M. Khoshgoftaar, Justin M. Johnson |
| 2022 | ICTAI | Exploring Language-Interfaced Fine-Tuning for COVID-19 Patient Survival Classification. | Connor Shorten, Erika Cardenas, Taghi M. Khoshgoftaar, Javad Hashemi, Safiya George Dalmida, David Newman, Debarshi Datta, Laurie Martinez, Candice Sareli, Paula Eckard |
| 2021 | ICMLA | Detecting SSH and FTP Brute Force Attacks in Big Data. | John T. Hancock, Taghi M. Khoshgoftaar, Joffrey L. Leevy |
| 2021 | ICMLA | Robust Thresholding Strategies for Highly Imbalanced and Noisy Data. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2021 | ICMLA | Detecting Information Theft Attacks in the Bot-IoT Dataset. | Joffrey L. Leevy, John T. Hancock, Taghi M. Khoshgoftaar, Jared M. Peterson |
| 2021 | ICMLA | KerasBERT: Modeling the Keras Language. | Connor Shorten, Taghi M. Khoshgoftaar |
| 2021 | ICMLA | Feature Popularity Between Different Web Attacks with Supervised Feature Selection Rankers. | Richard Zuech, John T. Hancock, Taghi M. Khoshgoftaar |
| 2021 | IRI | Using Inductive Transfer Learning to Improve Hotel Review Spam Detection. | Michael Crawford, Taghi M. Khoshgoftaar |
| 2021 | IRI | Impact of Hyperparameter Tuning in Classifying Highly Imbalanced Big Data. | John T. Hancock, Taghi M. Khoshgoftaar |
| 2021 | IRI | Encoding Techniques for High-Cardinality Features and Ensemble Learners. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2021 | IRI | Detecting Slow Application-Layer DoS Attacks With PCA. | Clifford Kemp, Chad Calvert, Taghi M. Khoshgoftaar |
| 2021 | IRI | Detecting Web Attacks in Severely Imbalanced Network Traffic Data. | Richard Zuech, John T. Hancock, Taghi M. Khoshgoftaar |
| 2021 | ICTAI | Output Thresholding for Ensemble Learners and Imbalanced Big Data. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2021 | ICTAI | The Effects of Class Label Noise on Highly-Imbalanced Big Data. | Robert K. L. Kennedy, Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2021 | ICTAI | Feature Extraction for Class Imbalance Using a Convolutional Autoencoder and Data Sampling. | Zahra Salekshahrezaee, Joffrey L. Leevy, Taghi M. Khoshgoftaar |
| 2021 | ICTAI | Investigating the Generalization of Image Classifiers with Augmented Test Sets. | Connor Shorten, Taghi M. Khoshgoftaar |
| 2020 | ICMLA | Evaluating The Number of Trainable Parameters on Deep Maxout and LReLU Networks for Visual Recognition. | Gabriel Castaneda, Paul Morris, Taghi M. Khoshgoftaar |
| 2020 | ICMLA | Performance of CatBoost and XGBoost in Medicare Fraud Detection. | John T. Hancock, Taghi M. Khoshgoftaar |
| 2020 | ICMLA | Accelerated Deep Learning on HPCC Systems. | Robert K. L. Kennedy, Taghi M. Khoshgoftaar |
| 2020 | IRI | Medicare Fraud Detection using CatBoost. | John T. Hancock, Taghi M. Khoshgoftaar |
| 2020 | IRI | Semantic Embeddings for Medical Providers and Fraud Detection. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2020 | IRI | Detection Methods of Slow Read DoS Using Full Packet Capture Data. | Clifford Kemp, Chad Calvert, Taghi M. Khoshgoftaar |
| 2019 | EDM | Differentiating between Educational Data Mining and Learning Analytics: A Bibliometric Approach. | Stevens Dormezil, Taghi M. Khoshgoftaar, Federica Robinson-Bryant |
| 2019 | FlAIRS | Detecting Slow HTTP POST DoS Attacks Using Netflow Features. | Chad Calvert, Clifford Kemp, Taghi M. Khoshgoftaar, Maryam M. Najafabadi |
| 2019 | FlAIRS | Investigation of Maxout Activations on Convolutional Neural Networks for Big Data Text Sentiment Analysis. | Gabriel Castaneda, Paul Morris, Joseph D. Prusa, Taghi M. Khoshgoftaar |
| 2019 | ICMLA | Deep Learning and Thresholding with Class-Imbalanced Big Data. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2019 | ICMLA | The Effect of Time on the Maintenance of a Predictive Model. | Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, Naeem Seliya |
| 2019 | ICMLA | Learning Curve Estimation with Large Imbalanced Datasets. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2019 | ICMLA | A Study on Software Metric Selection for Software Fault Prediction. | Huanjing Wang, Taghi M. Khoshgoftaar |
| 2019 | IRI | Evaluating Model Predictive Performance: A Medicare Fraud Detection Case Study. | Richard A. Bauder, Matthew Herland, Taghi M. Khoshgoftaar |
| 2019 | IRI | Deep Learning with Maxout Activations for Visual Recognition and Verification. | Gabriel Castaneda, Paul Morris, Taghi M. Khoshgoftaar |
| 2019 | IRI | A Comparison of Performance Metrics with Severely Imbalanced Network Security Big Data. | Tawfiq Hasanin, Taghi M. Khoshgoftaar, Joffrey L. Leevy |
| 2019 | IRI | Deep Learning and Data Sampling with Imbalanced Big Data. | Justin M. Johnson, Taghi M. Khoshgoftaar |
| 2019 | ICTAI | Threshold Based Optimization of Performance Metrics with Severely Imbalanced Big Security Data. | Chad Calvert, Taghi M. Khoshgoftaar |
| 2019 | ICTAI | Approximating Learning Curves for Imbalanced Big Data with Limited Labels. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2018 | FlAIRS | The Detection of Medicare Fraud Using Machine Learning Methods with Excluded Provider Labels. | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2018 | FlAIRS | Fraud Detection with a Limited Number of Known Fraudulent Medicare Providers. | Richard A. Bauder, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2018 | FlAIRS | Location-Based Twitter Sentiment Analysis for Predicting the U.S. 2016 Presidential Election. | Brian Heredia, Joseph D. Prusa, Taghi M. Khoshgoftaar |
| 2018 | ICMLA | An Empirical Study on Class Rarity in Big Data. | Richard A. Bauder, Taghi M. Khoshgoftaar, Tawfiq Hasanin |
| 2018 | IRI | A Survey of Medicare Data Processing and Integration for Fraud Detection. | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2018 | IRI | Medicare Fraud Detection Using Random Forest with Class Imbalanced Big Data. | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2018 | IRI | Identifying Medicare Provider Fraud with Unsupervised Machine Learning. | Richard A. Bauder, Raquel da Rosa, Taghi M. Khoshgoftaar |
| 2018 | IRI | The Effects of Random Undersampling with Simulated Class Imbalance for Big Data. | Tawfiq Hasanin, Taghi M. Khoshgoftaar |
| 2018 | IRI | Utilizing Netflow Data to Detect Slow Read Attacks. | Clifford Kemp, Chad Calvert, Taghi M. Khoshgoftaar |
| 2018 | IRI | Is Gene Selection Enough for Imbalanced Bioinformatics Data? | Ahmad Abu Shanab, Taghi M. Khoshgoftaar |
| 2018 | IRI | Filter-Based Subset Selection for Easy, Moderate, and Hard Bioinformatics Data. | Ahmad Abu Shanab, Taghi M. Khoshgoftaar |
| 2018 | ICTAI | Data Sampling Approaches with Severely Imbalanced Big Data for Medicare Fraud Detection. | Richard A. Bauder, Taghi M. Khoshgoftaar, Tawfiq Hasanin |
| 2018 | ICTAI | Building and Interpreting Risk Models from Imbalanced Clinical Data. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2017 | FlAIRS | Multivariate Anomaly Detection in Medicare using Model Residuals and Probabilistic Programming. | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2017 | FlAIRS | A Text Mining Approach for Anomaly Detection in Application Layer DDoS Attacks. | Maryam M. Najafabadi, Taghi M. Khoshgoftaar, Chad Calvert, Clifford Kemp |
| 2017 | FlAIRS | Deep Neural Network Architecture for Character-Level Learning on Short Text. | Joseph D. Prusa, Taghi M. Khoshgoftaar |
| 2017 | ICMLA | Medicare Fraud Detection Using Machine Learning Methods. | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2017 | ICMLA | Comparing Transfer Learning and Traditional Learning Under Domain Class Imbalance. | Karl R. Weiss, Taghi M. Khoshgoftaar |
| 2017 | IRI | Estimating Outlier Score Probabilities. | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2017 | IRI | Medical Provider Specialty Predictions for the Detection of Anomalous Medicare Insurance Claims. | Matthew Herland, Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2017 | IRI | Using Weather and Playing Surface to Predict the Occurrence of Injury in Major League Soccer Games: A Case Study. | Sara Landset, Michael F. Bergeron, Taghi M. Khoshgoftaar |
| 2017 | IRI | User Behavior Anomaly Detection for Application Layer DDoS Attacks. | Maryam M. Najafabadi, Taghi M. Khoshgoftaar, Chad Calvert, Clifford Kemp |
| 2017 | IRI | Extracting Knowledge from Technical Reports for the Valuation of West Texas Intermediate Crude Oil Futures. | Joseph D. Prusa, Ryan Sagul, Taghi M. Khoshgoftaar, Michael Sterling |
| 2017 | IRI | Modernizing Analytics for Melanoma with a Large-Scale Research Dataset. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2017 | IRI | Analysis of Transfer Learning Performance Measures. | Karl R. Weiss, Taghi M. Khoshgoftaar |
| 2017 | ICTAI | Training Convolutional Networks on Truncated Text. | Joseph D. Prusa, Taghi M. Khoshgoftaar |
| 2017 | ICTAI | Evaluation of Transfer Learning Algorithms Using Different Base Learners. | Karl R. Weiss, Taghi M. Khoshgoftaar |
| 2016 | FlAIRS | Reducing Feature Set Explosion to Facilitate Real-World Review Spam Detection. | Michael Crawford, Taghi M. Khoshgoftaar, Joseph D. Prusa |
| 2016 | FlAIRS | RUDY Attack: Detection at the Network Level and Its Important Features. | Maryam M. Najafabadi, Taghi M. Khoshgoftaar, Amri Napolitano, Charles Wheelus |
| 2016 | FlAIRS | Comparing Approaches for Combining Data Sampling and Feature Selection to Address Key Data Quality Issues in Tweet Sentiment Analysis. | Joseph D. Prusa, Taghi M. Khoshgoftaar |
| 2016 | FlAIRS | Necessity of Feature Selection when Augmenting Tweet Sentiment Feature Spaces with Emoticons. | Joseph D. Prusa, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2016 | FlAIRS | Enhancing Ensemble Learners with Data Sampling on High-Dimensional Imbalanced Tweet Sentiment Data. | Joseph D. Prusa, Taghi M. Khoshgoftaar, Naeem Seliya |
| 2016 | ICMLA | A Probabilistic Programming Approach for Outlier Detection in Healthcare Claims. | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2016 | ICMLA | An Investigation of Ensemble Techniques for Detection of Spam Reviews. | Brian Heredia, Taghi M. Khoshgoftaar, Joseph D. Prusa, Michael Crawford |
| 2016 | ICMLA | Investigating Transfer Learners for Robustness to Domain Class Imbalance. | Karl R. Weiss, Taghi M. Khoshgoftaar |
| 2016 | IRI | A Novel Method for Fraudulent Medicare Claims Detection from Expected Payment Deviations (Application Paper). | Richard A. Bauder, Taghi M. Khoshgoftaar |
| 2016 | IRI | Investigating the Variation of Ensemble Size on Bagging-Based Classifier Performance in Imbalanced Bioinformatics Datasets. | Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano |
| 2016 | IRI | Cross-Domain Sentiment Analysis: An Empirical Investigation. | Brian Heredia, Taghi M. Khoshgoftaar, Joseph D. Prusa, Michael Crawford |
| 2016 | IRI | Designing a Better Data Representation for Deep Neural Networks and Text Classification. | Joseph D. Prusa, Taghi M. Khoshgoftaar |
| 2016 | IRI | Predicting Cancer Relapse with Clinical Data: A Survey of Current Techniques. | Aaron N. Richter, Taghi M. Khoshgoftaar |
| 2016 | IRI | Designing a Testing Framework for Transfer Learning Algorithms (Application Paper). | Karl R. Weiss, Taghi M. Khoshgoftaar, Oneeb Rehman |
| 2016 | ICTAI | Predicting Medical Provider Specialties to Detect Anomalous Insurance Claims. | Richard A. Bauder, Taghi M. Khoshgoftaar, Aaron N. Richter, Matthew Herland |
| 2016 | ICTAI | An Investigation of Transfer Learning and Traditional Machine Learning Algorithms. | Karl R. Weiss, Taghi M. Khoshgoftaar |
| 2015 | FlAIRS | Selecting the Appropriate Ensemble Learning Approach for Balanced Bioinformatics Data. | David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2015 | FlAIRS | Impact of Feature Selection Techniques for Tweet Sentiment Classification. | Joseph D. Prusa, Taghi M. Khoshgoftaar, David J. Dittman |
| 2015 | FlAIRS | A New Intrusion Detection Benchmarking System. | Richard Zuech, Taghi M. Khoshgoftaar, Naeem Seliya, Maryam M. Najafabadi, Clifford Kemp |
| 2015 | ICMLA | Does the Inclusion of Data Sampling Improve the Performance of Boosting Algorithms on Imbalanced Bioinformatics Data? | Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano |
| 2015 | ICMLA | Investigating New Bootstrapping Approaches of Bagging Classifiers to Account for Class Imbalance in Bioinformatics Datasets. | Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano |
| 2015 | ICMLA | Detection of SSH Brute Force Attacks Using Aggregated Netflow Data. | Maryam M. Najafabadi, Taghi M. Khoshgoftaar, Chad Calvert, Clifford Kemp |
| 2015 | ICMLA | Utilizing Ensemble, Data Sampling and Feature Selection Techniques for Improving Classification Performance on Tweet Sentiment Data. | Joseph D. Prusa, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2015 | ICMLA | The Effect of Dataset Size on Training Tweet Sentiment Classifiers. | Joseph D. Prusa, Taghi M. Khoshgoftaar, Naeem Seliya |
| 2015 | IRI | A Survey of 2D Face Databases. | Gabriel Castaneda, Taghi M. Khoshgoftaar |
| 2015 | IRI | The Effect of Data Sampling When Using Random Forest on Imbalanced Bioinformatics Data. | David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2015 | IRI | Choosing an Appropriate Ensemble Classifier for Balanced Bioinformatics Data. | Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano |
| 2015 | IRI | Observing the Effect of the Choice of Classifier on Bioinformatics Data with Varying Levels of Data Quality and Class Balance. | Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Ahmad Abu Shanab |
| 2015 | IRI | Building an Effective Classification Model for Breast Cancer Patient Response Data. | Brian Heredia, Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman |
| 2015 | IRI | Alterations to the Bootstrapping Process within Random Forest: A Case Study on Imbalanced Bioinformatics Data. | Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano |
| 2015 | IRI | Using Ensemble Learners to Improve Classifier Performance on Tweet Sentiment Data. | Joseph D. Prusa, Taghi M. Khoshgoftaar, David J. Dittman |
| 2015 | IRI | Using Random Undersampling to Alleviate Class Imbalance on Tweet Sentiment Data. | Joseph D. Prusa, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano |
| 2015 | IRI | A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data. | Aaron N. Richter, Taghi M. Khoshgoftaar, Sara Landset, Tawfiq Hasanin |
| 2015 | ICTAI | Ensemble vs. Data Sampling: Which Option Is Best Suited to Improve Classification Performance of Imbalanced Bioinformatics Data? | Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano |
| 2015 | ICTAI | Using Feature Selection in Combination with Ensemble Learning Techniques to Improve Tweet Sentiment Classification Performance. | Joseph D. Prusa, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2015 | ICTAI | Efficient Modeling of User-Entity Preference in Big Social Networks. | Aaron N. Richter, Michael Crawford, Brian Heredia, Taghi M. Khoshgoftaar |
| 2014 | BIBE | Selecting the Appropriate Data Sampling Approach for Imbalanced and High-Dimensional Bioinformatics Datasets. | David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2014 | BIBE | Select-Bagging: Effectively Combining Gene Selection and Bagging for Balanced Bioinformatics Data. | David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano, Alireza Fazelpour |
| 2014 | BIBE | Effects of the Use of Boosting on Classification Performance of Imbalanced Bioinformatics Datasets. | Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano |
| 2014 | BIBE | Machine Learning for Detecting Brute Force Attacks at the Network Level. | Maryam M. Najafabadi, Taghi M. Khoshgoftaar, Clifford Kemp, Naeem Seliya, Richard Zuech |
| 2014 | BIBE | Evaluation of Wrapper-Based Feature Selection Using Hard, Moderate, and Easy Bioinformatics Data. | Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald |
| 2014 | BIBE | Using Correlation-Based Feature Selection for a Diverse Collection of Bioinformatics Datasets. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2014 | BIBE | Network Traffic Prediction Models for Near- and Long-Term Predictions. | Randall Wald, Taghi M. Khoshgoftaar, Richard Zuech, Amri Napolitano |
| 2014 | BIBE | A Session Based Approach for Aggregating Network Traffic Data - The SANTA Dataset. | Charles Wheelus, Taghi M. Khoshgoftaar, Richard Zuech, Maryam M. Najafabadi |
| 2014 | FlAIRS | Comparison of Data Sampling Approaches for Imbalanced Bioinformatics Data. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2014 | FlAIRS | Combining Feature Selection and Ensemble Learning for Software Quality Estimation. | Kehan Gao, Taghi M. Khoshgoftaar, Randall Wald |
| 2014 | FlAIRS | Optimizing Wrapper-Based Feature Selection for Use on Bioinformatics Data. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2014 | IRI | Classification performance of three approaches for combining data sampling and gene selection on bioinformatics data. | Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano |
| 2014 | IRI | Improving software quality estimation by combining feature selection strategies with sampled ensemble learning. | Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano |
| 2014 | IRI | Rotation invariant face recognition survey. | Gabriel Castaneda Oscos, Taghi M. Khoshgoftaar, Randall Wald |
| 2014 | IRI | How ranker and learner choice affects classification performance on noisy bioinformatics data. | Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2014 | IRI | The effect of noise level and distribution on classification of easy gene microarray data. | Randall Wald, Taghi M. Khoshgoftaar, Ahmad Abu Shanab |
| 2014 | IRI | Using feature selection and classification to build effective and efficient firewalls. | Randall Wald, Flavio Villanustre, Taghi M. Khoshgoftaar, Richard Zuech, Jarvis Robinson, Edin Muharemagic |
| 2014 | IRI | Stability of filter- and wrapper-based software metric selection techniques. | Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | FlAIRS | Classification Performance of Rank Aggregation Techniques for Ensemble Gene Selection. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2013 | FlAIRS | Ensemble Gene Selection Versus Single Gene Selection: Which Is Better? | Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman |
| 2013 | ICMLA | Simplifying the Utilization of Machine Learning Techniques for Bioinformatics. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2013 | ICMLA | Improving Software Quality Estimation by Combining Boosting and Feature Selection. | Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | ICMLA | Survey of Clinical Data Mining Applications on Big Data in Health Informatics. | Matthew Herland, Taghi M. Khoshgoftaar, Randall Wald |
| 2013 | ICMLA | Contrasting Undersampled Boosting with Internal and External Feature Selection for Patient Response Datasets. | Taghi M. Khoshgoftaar, David J. Dittman, Randall Wald, Amri Napolitano |
| 2013 | ICMLA | Survey of Data Cleansing and Monitoring for Large-Scale Battery Backup Installations. | Liz Aranguren Pachano, Taghi M. Khoshgoftaar, Randall Wald |
| 2013 | ICMLA | Random Forest with 200 Selected Features: An Optimal Model for Bioinformatics Research. | Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano |
| 2013 | ICMLA | Comparison of Stability for Different Families of Filter-Based and Wrapper-Based Feature Selection. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | ICMLA | Comparative Analysis on the Stability of Feature Selection Techniques Using Three Frameworks on Biological Datasets. | Randall Wald, Taghi M. Khoshgoftaar, Ahmad Abu Shanab, Amri Napolitano |
| 2013 | ICMLA | An Empirical Study on Wrapper-Based Feature Selection for Software Engineering Data. | Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | IRI | Comparison of rank-based vs. score-based aggregation for ensemble gene selection. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2013 | IRI | Gene selection stability's dependence on dataset difficulty. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2013 | IRI | A survey of stability analysis of feature subset selection techniques. | Taghi M. Khoshgoftaar, Alireza Fazelpour, Huanjing Wang, Randall Wald |
| 2013 | IRI | Feature list aggregation approaches for ensemble gene selection on patient response datasets. | Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, Amri Napolitano |
| 2013 | IRI | Patient response datasets: Challenges and opportunities. | Randall Wald, Taghi M. Khoshgoftaar |
| 2013 | IRI | The use of balance-aware subsampling for bioinformatics datasets. | Randall Wald, Taghi M. Khoshgoftaar, Alireza Fazelpour |
| 2013 | IRI | Hidden dependencies between class imbalance and difficulty of learning for bioinformatics datasets. | Randall Wald, Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman |
| 2013 | IRI | The importance of performance metrics within wrapper feature selection. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | IRI | Filter- and wrapper-based feature selection for predicting user interaction with Twitter bots. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | IRI | Predicting susceptibility to social bots on Twitter. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano, Chris Sumner |
| 2013 | ICTAI | Maximizing Classification Performance for Patient Response Datasets. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2013 | ICTAI | A Review of Ensemble Classification for DNA Microarrays Data. | Taghi M. Khoshgoftaar, David J. Dittman, Randall Wald, Wael Awada |
| 2013 | ICTAI | Stability of Filter- and Wrapper-Based Feature Subset Selection. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | ICTAI | How the Choice of Wrapper Learner and Performance Metric Affects Subset Evaluation. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | ICTAI | Should the Same Learners Be Used Both within Wrapper Feature Selection and for Building Classification Models? | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2013 | ICTAI | Which Users Reply to and Interact with Twitter Social Bots? | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano, Chris Sumner |
| 2013 | ICTAI | Comparison of Two Frameworks for Measuring the Stability of Gene-Selection Techniques on Noisy Class-Imbalanced Data. | Randall Wald, Taghi M. Khoshgoftaar, Ahmad Abu Shanab |
| 2012 | FlAIRS | Robustness of Threshold-Based Feature Rankers with Data Sampling on Noisy and Imbalanced Data. | Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald |
| 2012 | ICMLA | The Effect of Number of Iterations on Ensemble Gene Selection. | Wael Awada, Taghi M. Khoshgoftaar, David J. Dittman, Randall Wald |
| 2012 | ICMLA | Determining the Number of Iterations Appropriate for Ensemble Gene Selection on Microarray Data. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2012 | ICMLA | Comparing Two New Gene Selection Ensemble Approaches with the Commonly-Used Approach. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2012 | ICMLA | Decision Level Fusion of Wavelet Features for Ocean Turbine State Detection. | Janell Duhaney, Taghi M. Khoshgoftaar |
| 2012 | ICMLA | Studying the Effect of Class Imbalance in Ocean Turbine Fault Data on Reliable State Detection. | Janell Duhaney, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2012 | ICMLA | Applying Feature Selection to Short Time Wavelet Transformed Vibration Data for Reliability Analysis of an Ocean Turbine. | Janell Duhaney, Taghi M. Khoshgoftaar, Randall Wald |
| 2012 | ICMLA | A Hybrid Approach to Coping with High Dimensionality and Class Imbalance for Software Defect Prediction. | Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2012 | ICMLA | A Novel Noise-Resistant Boosting Algorithm for Class-Skewed Data. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2012 | ICMLA | First Order Statistics Based Feature Selection: A Diverse and Powerful Family of Feature Seleciton Techniques. | Taghi M. Khoshgoftaar, David J. Dittman, Randall Wald, Alireza Fazelpour |
| 2012 | ICMLA | Mean Aggregation versus Robust Rank Aggregation for Ensemble Gene Selection. | Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman |
| 2012 | ICMLA | A New Fixed-Overlap Partitioning Algorithm for Determining Stability of Bioinformatics Gene Rankers. | Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman |
| 2012 | ICMLA | Using Twitter Content to Predict Psychopathy. | Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano, Chris Sumner |
| 2012 | ICMLA | An Empirical Study on the Stability of Feature Selection for Imbalanced Software Engineering Data. | Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2012 | ICMLA | A Comparative Study on the Stability of Software Metric Selection Techniques. | Huanjing Wang, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2012 | IRI | A review of the stability of feature selection techniques for bioinformatics data. | Wael Awada, Taghi M. Khoshgoftaar, David J. Dittman, Randall Wald, Amri Napolitano |
| 2012 | IRI | Exploring an iterative feature selection technique for highly imbalanced data sets. | Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano |
| 2012 | IRI | Panel: Using information re-use and integration principles in big data. | Gordon K. Lee, Elisa Bertino, Stuart Harvey Rubin, Taghi M. Khoshgoftaar, Bhavani Thuraisingham, James D. McCaffrey |
| 2012 | IRI | Impact of noise and data sampling on stability of feature ranking techniques for biological datasets. | Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2012 | IRI | An extensive comparison of feature ranking aggregation techniques in bioinformatics. | Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman, Wael Awada, Amri Napolitano |
| 2012 | IRI | Machine prediction of personality from Facebook profiles. | Randall Wald, Taghi M. Khoshgoftaar, Chris Sumner |
| 2012 | IRI | A novel dataset-similarity-aware approach for evaluating stability of software metric selection techniques. | Huanjing Wang, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano |
| 2011 | FlAIRS | Robustness of Filter-Based Feature Ranking: A Case Study. | Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2011 | FlAIRS | Feature Level Sensor Fusion for Improved Fault Detection in MCM Systems for Ocean Turbines. | Janell Duhaney, Taghi M. Khoshgoftaar, John C. Sloan |
| 2011 | FlAIRS | How Many Software Metrics Should be Selected for Defect Prediction? | Huanjing Wang, Taghi M. Khoshgoftaar, Naeem Seliya |
| 2011 | ICMLA | Impact of Noise and Data Sampling on Stability of Feature Selection. | Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald |
| 2011 | ICMLA | Stability and Classification Performance of Feature Selection Techniques. | Huanjing Wang, Taghi M. Khoshgoftaar, Qianhui Althea Liang |
| 2011 | IRI | A noise-based stability evaluation of threshold-based feature selection techniques. | Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2011 | IRI | A comparative evaluation of feature ranking methods for high dimensional bioinformatics data. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2011 | IRI | Comparison of approaches to alleviate problems with high-dimensional and class-imbalanced data. | Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse |
| 2011 | IRI | Fourier transforms for vibration analysis: A review and case study. | Randall Wald, Taghi M. Khoshgoftaar, John C. Sloan |
| 2011 | IRI | Measuring robustness of Feature Selection techniques on software engineering datasets. | Huanjing Wang, Taghi M. Khoshgoftaar, Randall Wald |
| 2011 | ICTAI | Feature Selection on Dynamometer Data for Reliability Analysis. | Janell Duhaney, Taghi M. Khoshgoftaar, John C. Sloan |
| 2011 | ICTAI | Impact of Data Sampling on Stability of Feature Selection for Software Measurement Data. | Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2011 | ICTAI | Feature Selection for Vibration Sensor Data Transformed by a Streaming Wavelet Packet Decomposition. | Randall Wald, Taghi M. Khoshgoftaar, John C. Sloan |
| 2011 | ICTAI | Measuring Stability of Threshold-Based Feature Selection Techniques. | Huanjing Wang, Taghi M. Khoshgoftaar |
| 2010 | FlAIRS | An Evaluation of Sampling on Filter-Based Feature Selection Methods. | Kehan Gao, Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2010 | GRC | A Comparative Study of Threshold-Based Feature Selection Techniques. | Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2010 | ICMLA | Comparative Analysis of DNA Microarray Data through the Use of Feature Selection Techniques. | David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse |
| 2010 | ICMLA | A Novel Noise Filtering Algorithm for Imbalanced Data. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2010 | ICMLA | A Comparative Study of Ensemble Feature Selection Techniques for Software Defect Prediction. | Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2010 | IRI | Evaluating the impact of data quality on sampling. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2010 | IRI | A novel feature selection technique for highly imbalanced data. | Taghi M. Khoshgoftaar, Kehan Gao, Jason Van Hulse |
| 2010 | IRI | Active learning with neural networks for intrusion detection. | Naeem Seliya, Taghi M. Khoshgoftaar |
| 2010 | IRI | A comparative study of filter-based feature ranking techniques. | Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao |
| 2010 | ICTAI | Attribute Selection and Imbalanced Data: Problems in Software Defect Prediction. | Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya |
| 2009 | FlAIRS | VipBoost: A More Accurate Boosting Algorithm. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner |
| 2009 | ICDM | Feature Selection with High-Dimensional Imbalanced Data. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald |
| 2009 | ICDM | Mining Data from Multiple Software Development Projects. | Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya |
| 2009 | ICMLA | Wrapper-Based Feature Ranking for Software Engineering Metrics. | Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2009 | ICMLA | Feature Selection with Imbalanced Data for Software Defect Prediction. | Taghi M. Khoshgoftaar, Kehan Gao |
| 2009 | IRI | An Empirical Investigation of Filter Attribute Selection Techniques for Software Quality Classification. | Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang |
| 2009 | IRI | An Empirical Comparison of Repetitive Undersampling Techniques. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2009 | IRI | Aggregating Performance Metrics for Classifier Evaluation. | Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2009 | ICTAI | An Empirical Study on Wrapper-Based Feature Ranking. | Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2009 | ICTAI | Exploring Software Quality Classification with a Wrapper-Based Feature Ranking Technique. | Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2009 | ICTAI | A Study on the Relationships of Classifier Performance Metrics. | Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2009 | ICTAI | High-Dimensional Software Engineering Data and Feature Selection. | Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya |
| 2008 | CEC | Software quality modeling: The impact of class noise on the random forest classifier. | Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Lofton A. Bullard |
| 2008 | FlAIRS | Building Useful Models from Imbalanced Data with Sampling and Boosting. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano |
| 2008 | FlAIRS | Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction. | Chinar C. Shah, Xingquan Zhu, Taghi M. Khoshgoftaar, Justin Beyer |
| 2008 | FlAIRS | A Mixture Imputation-Boosted Collaborative Filter. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner |
| 2008 | ICDM | A Comparative Study of Data Sampling and Cost Sensitive Learning. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano |
| 2008 | ICMLA | Comparison of Four Performance Metrics for Evaluating Sampling Techniques for Low Quality Class-Imbalanced Data. | Andres Folleco, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2008 | ICPR | RUSBoost: Improving classification performance when training data is skewed. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano |
| 2008 | ICPR | VoB predictors: Voting on bagging classifications. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu |
| 2008 | IRI | Identifying learners robust to low quality data. | Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Lofton A. Bullard |
| 2008 | IRI | Hybrid sampling for imbalanced data. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2008 | IRI | VCI predictors: Voting on classifications from imputed learning sets. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu |
| 2008 | ICTAI | Resampling or Reweighting: A Comparison of Boosting Implementations. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano |
| 2008 | ICTAI | Improving Learner Performance with Data Sampling and Boosting. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano |
| 2008 | ICTAI | Addressing Class Imbalance in Non-binary Classification Problems. | Naeem Seliya, Zhiwei Xu, Taghi M. Khoshgoftaar |
| 2008 | ICTAI | Using Imputation Techniques to Help Learn Accurate Classifiers. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greiner |
| 2007 | FlAIRS | Low-Effort Labeling of Network Events for Intrusion Detection in WLANs. | Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya |
| 2007 | ICDM | Skewed Class Distributions and Mislabeled Examples. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2007 | ICIP | Arbitrarily-Shaped Window Based Stereo Matching using the Go-Light Optimization Algorithm. | Xiaoyuan Su, Taghi M. Khoshgoftaar |
| 2007 | ICML | Experimental perspectives on learning from imbalanced data. | Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano |
| 2007 | ICMLA | An application of a rule-based model in software quality classification. | Lofton A. Bullard, Taghi M. Khoshgoftaar, Kehan Gao |
| 2007 | ICMLA | Using evolutionary sampling to mine imbalanced data. | Dennis J. Drown, Taghi M. Khoshgoftaar, Ramaswamy Narayanan |
| 2007 | ICMLA | Learning with limited minority class data. | Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse, Amri Napolitano, Andres Folleco |
| 2007 | IJCAI | An Empirical Study of the Noise Impact on Cost-Sensitive Learning. | Xingquan Zhu, Xindong Wu, Taghi M. Khoshgoftaar, Yong Shi |
| 2007 | IRI | Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data. | Jason Van Hulse, Taghi M. Khoshgoftaar |
| 2007 | IRI | Building a Novel GP-Based Software Quality Classifier Using Multiple Validation Datasets. | Yi Liu, Taghi M. Khoshgoftaar, Jenq-Foung JF Yao |
| 2007 | IRI | An Empirical Study on Estimating Motions in Video Stabilization. | Qiming Luo, Taghi M. Khoshgoftaar |
| 2007 | IRI | An Empirical Study of the Classification Performance of Learners on Imbalanced and Noisy Software Quality Data. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco |
| 2007 | ICTAI | An Empirical Study of Learning from Imbalanced Data Using Random Forest. | Taghi M. Khoshgoftaar, Moiz Golawala, Jason Van Hulse |
| 2007 | ICTAI | Mining Data with Rare Events: A Case Study. | Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano |
| 2006 | ICMLA | A Comparison of Software Fault Imputation Procedures. | Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert |
| 2006 | IRI | Noise correction using bayesian multiple imputation. | Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert, Lili Zhao |
| 2006 | IRI | Software quality imputation in the presence of noisy data. | Taghi M. Khoshgoftaar, Andres Folleco, Jason Van Hulse, Lofton A. Bullard |
| 2006 | IRI | Labeling network event records for intrusion detection in a Wireless LAN. | Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya |
| 2006 | IRI | Developing an effective validation strategy for genetic programming models based on multiple datasets. | Yi Liu, Taghi M. Khoshgoftaar, Jenq-Foung JF Yao |
| 2006 | IRI | Classification of ships in surveillance video. | Qiming Luo, Taghi M. Khoshgoftaar, Andres Folleco |
| 2006 | ICTAI | Assessment of a Multi-Strategy Classifier for an Embedded Software System. | Taghi M. Khoshgoftaar, Kehan Gao |
| 2006 | ICTAI | A Hybrid Approach to Cleansing Software Measurement Data. | Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert |
| 2006 | ICTAI | Collaborative Filtering for Multi-class Data Using Belief Nets Algorithms. | Xiaoyuan Su, Taghi M. Khoshgoftaar |
| 2005 | ICMLA | Identifying noise in an attribute of interest. | Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2005 | ICMLA | Intrusion detection in wireless networks using clustering techniques with expert analysis. | Taghi M. Khoshgoftaar, Shyam Varan Nath, Shi Zhong, Naeem Seliya |
| 2005 | IRI | Empirical case studies in attribute noise detection. | Taghi M. Khoshgoftaar, Jason Van Hulse |
| 2005 | IRI | Hierarchical indexing of ocean survey video by mean shift clustering and MDL principle. | Qiming Luo, Taghi M. Khoshgoftaar, Edgar An |
| 2005 | IRI | The partitioning- and rule-based filter for noise detection. | Yudong Xiao, Taghi M. Khoshgoftaar, Naeem Seliya |
| 2005 | IRI | Application of fuzzy expert system in test case selection for system regression test. | Zhiwei Xu, Kehan Gao, Taghi M. Khoshgoftaar |
| 2005 | ICTAI | A Clustering Approach to Wireless Network Intrusion Detection. | Shi Zhong, Taghi M. Khoshgoftaar, Shyam Varan Nath |
| 2004 | IRI | Generating Multiple Noise Elimination Filters with the Ensemble-Partitioning Filter. | Taghi M. Khoshgoftaar, Pierre Rebours |
| 2004 | IRI | Rule-Based Noise Detection for Software Measurement Data. | Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao |
| 2004 | ICTAI | Efficient Image Segmentation by Mean Shift Clustering and MDL-Guided Region Merging. | Qiming Luo, Taghi M. Khoshgoftaar |
| 2004 | ICTAI | Semi-Supervised Learning for Software Quality Estimation. | Naeem Seliya, Taghi M. Khoshgoftaar, Shi Zhong |
| 2004 | ICTAI | Noise Identification with the k-Means Algorithm. | Wei Tang, Taghi M. Khoshgoftaar |
| 2003 | GECCO | Building Decision Tree Software Quality Classification Models Using Genetic Programming. | Yi Liu, Taghi M. Khoshgoftaar |
| 2003 | ICCBR | Detecting Outliers Using Rule-Based Modeling for Improving CBR-Based Software Quality Classification Models. | Taghi M. Khoshgoftaar, Lofton A. Bullard, Kehan Gao |
| 2003 | ICTAI | Genetic Programming-Based Decision Trees for Software Quality Classification. | Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya |
| 2003 | ICTAI | Application of an Attribute Selection Method to CBR-Based Software Quality Classification. | Taghi M. Khoshgoftaar, Laurent A. Nguyen, Kehan Gao, Jayanth Rajeevalochanam |
| 2002 | ICTAI | Software Quality Classification Modeling Using The SPRINT Decision Tree Algorithm. | Taghi M. Khoshgoftaar, Naeem Seliya |
| 2002 | ISSRE | Improving Usefulness of Software Quality Classification Models Based on Boolean Discriminant Functions. | Taghi M. Khoshgoftaar |
| 2000 | ICTAI | Modeling software quality: the Software Measurement Analysis and Reliability Toolkit. | Taghi M. Khoshgoftaar, Edward B. Allen, Jason C. Busboom |
| 1999 | FlAIRS | Using Genetic Programming to Determine Software Quality. | Matthew P. Evett, Taghi M. Khoshgoftaar, Pei-der Chien, Edward B. Allen |
| 1999 | GECCO | Modelling software quality with GP. | Matthew P. Evett, Taghi M. Khoshgoftaar, Pei-der Chien, Edward B. Allen |
| 1999 | ISSRE | Classification tree models of software quality over multiple releases. | Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, John P. Hudepohl |
| 1998 | ISSRE | Predicting the order of fault-prone modules in legacy software. | Taghi M. Khoshgoftaar, Edward B. Allen |
| 1997 | ISSRE | Evolutionary neural networks: a robust approach to software reliability problems. | Robert Hochman, Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl |
| 1996 | ISSRE | Using the genetic algorithm to build optimal neural networks for fault-prone module detection. | Robert Hochman, Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl |
| 1996 | ISSRE | Integrating metrics and models for software risk assessment. | John P. Hudepohl, Stephen J. Aud, Taghi M. Khoshgoftaar, Edward B. Allen, Jean Mayrand |
| 1996 | ISSRE | Detection of software modules with high debug code churn in a very large legacy system. | Taghi M. Khoshgoftaar, Edward B. Allen, Nishith Goel, Amit Nandi, John McMullan |
| 1995 | ICECCS | Multivariate assessment of complex software systems: a comparative study. | Taghi M. Khoshgoftaar, Edward B. Allen |
| 1990 | COMPSAC | The lines of code metric as a predictor of program faults: a critical analysis. | Taghi M. Khoshgoftaar, John C. Munson |
| 1989 | ICSE | The Dimensionality of Program Complexity. | John C. Munson, Taghi M. Khoshgoftaar |