Amri Napolitano

110 papers A* 2B 10C 23Misc 32Journal 16Unranked 25

Year	Rank	Type	Title / Venue / Authors
2018	Misc	`conf`	Fraud Detection with a Limited Number of Known Fraudulent Medicare Providers. FLAIRS Richard A. Bauder, Taghi M. Khoshgoftaar, Amri Napolitano
2016	Misc	`conf`	Investigating the Variation of Ensemble Size on Bagging-Based Classifier Performance in Imbalanced Bioinformatics Datasets. IRI Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano
2016	—	`ch.`	Is Data Sampling Required When Using Random Forest for Classification on Imbalanced Bioinformatics Data? Theoretical Information Reuse and Integration David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano
2016	Misc	`conf`	Necessity of Feature Selection when Augmenting Tweet Sentiment Feature Spaces with Emoticons. FLAIRS Joseph D. Prusa, Taghi M. Khoshgoftaar, Amri Napolitano
2016	Misc	`conf`	RUDY Attack: Detection at the Network Level and Its Important Features. FLAIRS Maryam M. Najafabadi, Taghi M. Khoshgoftaar, Amri Napolitano, Charles Wheelus
2015	J	`jnl`	Aggregating Data Sampling with Feature Subset Selection to Address Skewed Software Defect Data. Int. J. Softw. Eng. Knowl. Eng. Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2015	Misc	`conf`	Alterations to the Bootstrapping Process within Random Forest: A Case Study on Imbalanced Bioinformatics Data. IRI Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano
2015	J	`jnl`	An Empirical Investigation on Wrapper-Based Feature Selection for Predicting Software Quality. Int. J. Softw. Eng. Knowl. Eng. Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2015	Misc	`conf`	Choosing an Appropriate Ensemble Classifier for Balanced Bioinformatics Data. IRI Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano
2015	C	`conf`	Combining Feature Subset Selection and Data Sampling for Coping with Highly Imbalanced Software Data. SEKE Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2015	C	`conf`	Does the Inclusion of Data Sampling Improve the Performance of Boosting Algorithms on Imbalanced Bioinformatics Data? ICMLA Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano
2015	B	`conf`	Ensemble vs. Data Sampling: Which Option Is Best Suited to Improve Classification Performance of Imbalanced Bioinformatics Data? ICTAI Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano
2015	C	`conf`	Investigating New Bootstrapping Approaches of Bagging Classifiers to Account for Class Imbalance in Bioinformatics Datasets. ICMLA Alireza Fazelpour, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano
2015	J	`jnl`	Investigating Two Approaches for Adding Feature Ranking to Sampled Ensemble Learning for Software Quality Estimation. Int. J. Softw. Eng. Knowl. Eng. Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2015	Misc	`conf`	Selecting the Appropriate Ensemble Learning Approach for Balanced Bioinformatics Data. FLAIRS David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano
2015	C	`conf`	Stability of Three Forms of Feature Selection Methods on Software Engineering Data. SEKE Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2015	Misc	`conf`	The Effect of Data Sampling When Using Random Forest on Imbalanced Bioinformatics Data. IRI David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano
2015	B	`conf`	Using Feature Selection in Combination with Ensemble Learning Techniques to Improve Tweet Sentiment Classification Performance. ICTAI Joseph D. Prusa, Taghi M. Khoshgoftaar, Amri Napolitano
2015	Misc	`conf`	Using Random Undersampling to Alleviate Class Imbalance on Tweet Sentiment Data. IRI Joseph D. Prusa, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano
2015	C	`conf`	Utilizing Ensemble, Data Sampling and Feature Selection Techniques for Improving Classification Performance on Tweet Sentiment Data. ICMLA Joseph D. Prusa, Taghi M. Khoshgoftaar, Amri Napolitano
2014	J	`jnl`	A comparative study of iterative and non-iterative feature selection techniques for software defect prediction. Inf. Syst. Frontiers Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano, Randall Wald
2014	C	`conf`	Choosing the Best Classification Performance Metric for Wrapper-based Software Metric Selection for Defect Prediction. SEKE Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2014	Misc	`conf`	Classification performance of three approaches for combining data sampling and gene selection on bioinformatics data. IRI Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano
2014	C	`conf`	Comparing Two Approaches for Adding Feature Ranking to Sampled Ensemble Learning for Software Quality Estimation. SEKE Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2014	Misc	`conf`	Comparison of Data Sampling Approaches for Imbalanced Bioinformatics Data. FLAIRS David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2014	C	`conf`	Effects of the Use of Boosting on Classification Performance of Imbalanced Bioinformatics Datasets. BIBE Taghi M. Khoshgoftaar, Alireza Fazelpour, David J. Dittman, Amri Napolitano
2014	Misc	`conf`	How ranker and learner choice affects classification performance on noisy bioinformatics data. IRI Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2014	Misc	`conf`	Improving software quality estimation by combining feature selection strategies with sampled ensemble learning. IRI Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano
2014	C	`conf`	Network Traffic Prediction Models for Near- and Long-Term Predictions. BIBE Randall Wald, Taghi M. Khoshgoftaar, Richard Zuech, Amri Napolitano
2014	Misc	`conf`	Optimizing Wrapper-Based Feature Selection for Use on Bioinformatics Data. FLAIRS Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2014	C	`conf`	Select-Bagging: Effectively Combining Gene Selection and Bagging for Balanced Bioinformatics Data. BIBE David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano, Alireza Fazelpour
2014	C	`conf`	Selecting the Appropriate Data Sampling Approach for Imbalanced and High-Dimensional Bioinformatics Datasets. BIBE David J. Dittman, Taghi M. Khoshgoftaar, Amri Napolitano
2014	Misc	`conf`	Stability of filter- and wrapper-based software metric selection techniques. IRI Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2014	J	`jnl`	The Use of Ensemble-Based Data Preprocessing Techniques for Software Defect Prediction. Int. J. Softw. Eng. Knowl. Eng. Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2014	C	`conf`	Using Correlation-Based Feature Selection for a Diverse Collection of Bioinformatics Datasets. BIBE Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2013	C	`conf`	A Study on First Order Statistics-Based Feature Selection Techniques on Software Metric Data. SEKE Huanjing Wang, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2013	—	`conf`	An Empirical Study on Wrapper-Based Feature Selection for Software Engineering Data. ICMLA (2) Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2013	Misc	`conf`	Classification Performance of Rank Aggregation Techniques for Ensemble Gene Selection. FLAIRS David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2013	—	`conf`	Comparative Analysis on the Stability of Feature Selection Techniques Using Three Frameworks on Biological Datasets. ICMLA (1) Randall Wald, Taghi M. Khoshgoftaar, Ahmad Abu Shanab, Amri Napolitano
2013	—	`conf`	Comparison of Stability for Different Families of Filter-Based and Wrapper-Based Feature Selection. ICMLA (2) Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2013	Misc	`conf`	Comparison of rank-based vs. score-based aggregation for ensemble gene selection. IRI David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2013	—	`conf`	Contrasting Undersampled Boosting with Internal and External Feature Selection for Patient Response Datasets. ICMLA (2) Taghi M. Khoshgoftaar, David J. Dittman, Randall Wald, Amri Napolitano
2013	C	`conf`	Exploring Ensemble-Based Data Preprocessing Techniques for Software Quality Estimation. SEKE Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2013	Misc	`conf`	Feature list aggregation approaches for ensemble gene selection on patient response datasets. IRI Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, Amri Napolitano
2013	Misc	`conf`	Filter- and wrapper-based feature selection for predicting user interaction with Twitter bots. IRI Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2013	Misc	`conf`	Gene selection stability's dependence on dataset difficulty. IRI David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2013	B	`conf`	How the Choice of Wrapper Learner and Performance Metric Affects Subset Evaluation. ICTAI Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2013	—	`conf`	Improving Software Quality Estimation by Combining Boosting and Feature Selection. ICMLA (1) Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2013	B	`conf`	Maximizing Classification Performance for Patient Response Datasets. ICTAI David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2013	Misc	`conf`	Predicting susceptibility to social bots on Twitter. IRI Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano, Chris Sumner
2013	—	`conf`	Random Forest with 200 Selected Features: An Optimal Model for Bioinformatics Research. ICMLA (1) Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano
2013	B	`conf`	Should the Same Learners Be Used Both within Wrapper Feature Selection and for Building Classification Models? ICTAI Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2013	—	`conf`	Simplifying the Utilization of Machine Learning Techniques for Bioinformatics. ICMLA (2) David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2013	B	`conf`	Stability of Filter- and Wrapper-Based Feature Subset Selection. ICTAI Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2013	Misc	`conf`	The importance of performance metrics within wrapper feature selection. IRI Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano
2013	B	`conf`	Which Users Reply to and Interact with Twitter Social Bots? ICTAI Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano, Chris Sumner
2012	—	`conf`	A Comparative Study on the Stability of Software Metric Selection Techniques. ICMLA (2) Huanjing Wang, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2012	—	`conf`	A Hybrid Approach to Coping with High Dimensionality and Class Imbalance for Software Defect Prediction. ICMLA (2) Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2012	—	`conf`	A Novel Noise-Resistant Boosting Algorithm for Class-Skewed Data. ICMLA (2) Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2012	Misc	`conf`	A novel dataset-similarity-aware approach for evaluating stability of software metric selection techniques. IRI Huanjing Wang, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2012	Misc	`conf`	A review of the stability of feature selection techniques for bioinformatics data. IRI Wael Awada, Taghi M. Khoshgoftaar, David J. Dittman, Randall Wald, Amri Napolitano
2012	J	`jnl`	An Empirical Study of Feature Ranking Techniques for Software Quality Prediction. Int. J. Softw. Eng. Knowl. Eng. Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano
2012	C	`conf`	An Empirical Study of Software Metric Selection Techniques for Defect Prediction. SEKE Huanjing Wang, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2012	—	`conf`	An Empirical Study on the Stability of Feature Selection for Imbalanced Software Engineering Data. ICMLA (1) Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2012	Misc	`conf`	An extensive comparison of feature ranking aggregation techniques in bioinformatics. IRI Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman, Wael Awada, Amri Napolitano
2012	—	`conf`	Comparing Two New Gene Selection Ensemble Approaches with the Commonly-Used Approach. ICMLA (2) David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2012	—	`conf`	Determining the Number of Iterations Appropriate for Ensemble Gene Selection on Microarray Data. ICMLA (1) David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2012	Misc	`conf`	Exploring an iterative feature selection technique for highly imbalanced data sets. IRI Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano
2012	Misc	`conf`	Impact of noise and data sampling on stability of feature ranking techniques for biological datasets. IRI Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2012	J	`jnl`	Measuring stability of feature ranking techniques: a noise-based approach. Int. J. Bus. Intell. Data Min. Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano
2012	—	`conf`	Similarity analysis of feature ranking techniques on imbalanced DNA microarray datasets. BIBM David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2012	J	`jnl`	Software measurement data reduction using ensemble techniques. Neurocomputing Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2012	C	`conf`	Stability of Filter-Based Feature Selection Methods for Imbalanced Software Measurement Data. SEKE Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2012	—	`conf`	Studying the Effect of Class Imbalance in Ocean Turbine Fault Data on Reliable State Detection. ICMLA (1) Janell Duhaney, Taghi M. Khoshgoftaar, Amri Napolitano
2012	J	`jnl`	Threshold-based feature selection techniques for high-dimensional bioinformatics data. Netw. Model. Anal. Health Informatics Bioinform. Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald
2012	—	`conf`	Using Twitter Content to Predict Psychopathy. ICMLA (2) Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano, Chris Sumner
2011	C	`conf`	A Comparative Study of Different Strategies for Predicting Software Quality. SEKE Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano
2011	Misc	`conf`	A comparative evaluation of feature ranking methods for high dimensional bioinformatics data. IRI Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2011	Misc	`conf`	A noise-based stability evaluation of threshold-based feature selection techniques. IRI Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano
2011	C	`conf`	An Empirical Study of Software Metrics Selection Using Support Vector Machine. SEKE Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2011	J	`jnl`	An exploration of learning when data is noisy and imbalanced. Intell. Data Anal. Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2011	J	`jnl`	Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data. IEEE Trans. Syst. Man Cybern. Part A Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2011	J	`jnl`	Evaluating the Impact of Data Quality on Sampling. J. Inf. Knowl. Manag. Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2011	B	`conf`	Impact of Data Sampling on Stability of Feature Selection for Software Measurement Data. ICTAI Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2011	—	`conf`	Random forest: A reliable tool for patient response prediction. BIBM Workshops David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Amri Napolitano
2011	—	`conf`	Using Classifier-Based Nominal Imputation to Improve Machine Learning. PAKDD (1) Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Amri Napolitano
2010	C	`conf`	A Comparative Study of Ensemble Feature Selection Techniques for Software Defect Prediction. ICMLA Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano
2010	C	`conf`	A Novel Noise Filtering Algorithm for Imbalanced Data. ICMLA Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2010	J	`jnl`	An Empirical Evaluation of Repetitive Undersampling Techniques. Int. J. Softw. Eng. Knowl. Eng. Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2010	—	`conf`	An Empirical Study of Predictive Modeling Techniques of Software Quality. BIONETICS Taghi M. Khoshgoftaar, Kehan Gao, Amri Napolitano
2010	Misc	`conf`	Evaluating the impact of data quality on sampling. IRI Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2010	J	`jnl`	RUSBoost: A Hybrid Approach to Alleviating Class Imbalance. IEEE Trans. Syst. Man Cybern. Part A Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2010	J	`jnl`	Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors. IEEE Trans. Neural Networks Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2009	Misc	`conf`	An Empirical Comparison of Repetitive Undersampling Techniques. IRI Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2009	—	`—`	Classification techniques for noisy and imbalanced data. Amri Napolitano
2009	B	`conf`	Exploring Software Quality Classification with a Wrapper-Based Feature Ranking Technique. ICTAI Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano
2009	—	`conf`	Feature Selection with High-Dimensional Imbalanced Data. ICDM Workshops Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald
2009	J	`jnl`	Identifying Learners Robust to Low Quality Data. Informatica (Slovenia) Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2009	C	`conf`	Wrapper-Based Feature Ranking for Software Engineering Metrics. ICMLA Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano
2008	—	`conf`	A Comparative Study of Data Sampling and Cost Sensitive Learning. ICDM Workshops Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008	Misc	`conf`	Building Useful Models from Imbalanced Data with Sampling and Boosting. FLAIRS Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008	C	`conf`	Comparison of Four Performance Metrics for Evaluating Sampling Techniques for Low Quality Class-Imbalanced Data. ICMLA Andres Folleco, Taghi M. Khoshgoftaar, Amri Napolitano
2008	—	`conf`	Improving Learner Performance with Data Sampling and Boosting. ICTAI (1) Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008	B	`conf`	RUSBoost: Improving classification performance when training data is skewed. ICPR Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008	—	`conf`	Resampling or Reweighting: A Comparison of Boosting Implementations. ICTAI (1) Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2007	A*	`conf`	Experimental perspectives on learning from imbalanced data. ICML Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2007	C	`conf`	Learning with limited minority class data. ICMLA Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse, Amri Napolitano, Andres Folleco
2007	—	`conf`	Mining Data with Rare Events: A Case Study. ICTAI (2) Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2007	—	`conf`	Skewed Class Distributions and Mislabeled Examples. ICDM Workshops Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
1982	A*	`conf`	An interactive drafting system based on two dimensional primitives. DAC G. Cosmai, Umberto Cugini, Piero Mussio, Amri Napolitano