Daniel P. Berrar
Orcid: 0000-0002-7038-2601Affiliations:
- Tokyo Institute of Technology, Interdisciplinary Graduate School of Science and Engineering
According to our database1,
Daniel P. Berrar
authored at least 39 papers
between 2003 and 2024.
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Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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on orcid.org
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on id.loc.gov
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on d-nb.info
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on berrar.com
On csauthors.net:
Bibliography
2024
A data- and knowledge-driven framework for developing machine learning models to predict soccer match outcomes.
Mach. Learn., October, 2024
2022
Data Min. Knowl. Discov., 2022
2021
Expert Syst. Appl., 2021
2020
SOINN+, a Self-Organizing Incremental Neural Network for Unsupervised Learning from Noisy Data Streams.
Expert Syst. Appl., 2020
2019
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019
Mach. Learn., 2019
Int. J. Data Sci. Anal., 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
2017
Confidence curves: an alternative to null hypothesis significance testing for the comparison of classifiers.
Mach. Learn., 2017
Int. J. Data Sci. Anal., 2017
On the Jeffreys-Lindley Paradox and the Looming Reproducibility Crisis in Machine Learning.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017
2016
Knowl. Inf. Syst., 2016
Proceedings of the Neural Information Processing - 23rd International Conference, 2016
2014
J. Mach. Learn. Res., 2014
J. Artif. Intell. Res., 2014
2013
Kybernetes, 2013
Significance tests or confidence intervals: which are preferable for the comparison of classifiers?
J. Exp. Theor. Artif. Intell., 2013
2012
Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them).
Briefings Bioinform., 2012
Null QQ plots: A simple graphical alternative to significance testing for the comparison of classifiers.
Proceedings of the 21st International Conference on Pattern Recognition, 2012
2011
Multidimensional scaling with discrimination coefficients for supervised visualization of high-dimensional data.
Neural Comput. Appl., 2011
J. Adv. Comput. Intell. Intell. Informatics, 2011
2010
Artificial Intelligence in Neuroscience and Systems Biology: Lessons Learnt, Open Problems, and the Road Ahead.
Adv. Artif. Intell., 2010
2006
Text mining of full-text journal articles combined with gene expression analysis reveals a relationship between sphingosine-1-phosphate and invasiveness of a glioblastoma cell line.
BMC Bioinform., 2006
BMC Bioinform., 2006
Proceedings of the Artificial Intelligence in Theory and Practice, 2006
Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2006
2005
Survival Trees for Analyzing Clinical Outcome in Lung Adenocarcinomas Based on Gene Expression Profiles: Identification of Neogenin and Diacylglycerol Kinase Expression as Critical Factors.
J. Comput. Biol., 2005
Proceedings of the 5th International Symposium on Cluster Computing and the Grid (CCGrid 2005), 2005
2003
Multiclass Cancer Classification Using Gene Expression Profiling and Probabilistic Neural Networks.
Proceedings of the 8th Pacific Symposium on Biocomputing, 2003
A Probabilistic Neural Network for Gene Selection and Classification of Microarray Data.
Proceedings of the International Conference on Artificial Intelligence, 2003