Chris Seiffert

发表

RUSBoost: Improving classification performance when training data is skewed

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 19th International Conference on Pattern Recognition.

Noise Correction using Bayesian Multiple Imputation

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, 2006 IEEE International Conference on Information Reuse & Integration.

A Comparative Study of Data Sampling and Cost Sensitive Learning

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 IEEE International Conference on Data Mining Workshops.

Low-Effort Labeling of Network Events for Intrusion Detection in WLANs

Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya, 2008, Int. J. Artif. Intell. Tools.

Improving Software-Quality Predictions With Data Sampling and Boosting

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

Mining Data with Rare Events: A Case Study

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007).

An empirical study of the classification performance of learners on imbalanced and noisy software quality data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2014, Inf. Sci..

Resampling or Reweighting: A Comparison of Boosting Implementations

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

Hybrid sampling for imbalanced data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2009, Integr. Comput. Aided Eng..

An Empirical Study of the Classification Performance of Learners on Imbalanced and Noisy Software Quality Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, 2007 IEEE International Conference on Information Reuse and Integration.

Learning with limited minority class data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, Sixth International Conference on Machine Learning and Applications (ICMLA 2007).

RUSBoost: A Hybrid Approach to Alleviating Class Imbalance

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

A Hybrid Approach to Cleansing Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06).

Polishing Noise in Continuous Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, International Conference on Software Engineering and Knowledge Engineering.

Hybrid sampling for imbalanced data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 IEEE International Conference on Information Reuse and Integration.

Building Useful Models from Imbalanced Data with Sampling and Boosting

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, FLAIRS.

Labeling Network Event Records for Intrusion Detection in aWireless LAN

Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya, 2006, 2006 IEEE International Conference on Information Reuse & Integration.

Learning from Software Quality Data with Class Imbalance and Noise

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, SEKE.

A Comparison of Software Fault Imputation Procedures

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, 2006 5th International Conference on Machine Learning and Applications (ICMLA'06).

The multiple imputation quantitative noise corrector

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, Intell. Data Anal..

Improving Learner Performance with Data Sampling and Boosting

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.