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ORCIDDaniel P. Berrar
Person information
- affiliation: Tokyo Institute of Technology, Interdisciplinary Graduate School of Science and Engineering
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Journal Articles
- 2022
[j25]Daniel Berrar
:
Using p-values for the comparison of classifiers: pitfalls and alternatives. Data Min. Knowl. Discov. 36(3): 1102-1139 (2022)- 2021
- [j24]Daniel Berrar, Werner Dubitzky:
Deep learning in bioinformatics and biomedicine. Briefings Bioinform. 22(2): 1513-1514 (2021) - [j23]Chayut Wiwatcharakoses, Daniel Berrar:
A self-organizing incremental neural network for continual supervised learning. Expert Syst. Appl. 185: 115662 (2021) - 2020
- [j22]Chayut Wiwatcharakoses, Daniel Berrar:
SOINN+, a Self-Organizing Incremental Neural Network for Unsupervised Learning from Noisy Data Streams. Expert Syst. Appl. 143 (2020) - 2019
- [j21]Daniel Berrar, Werner Dubitzky:
Should significance testing be abandoned in machine learning? Int. J. Data Sci. Anal. 7(4): 247-257 (2019) - [j20]Daniel Berrar, Philippe Lopes, Jesse Davis, Werner Dubitzky:
Guest editorial: special issue on machine learning for soccer. Mach. Learn. 108(1): 1-7 (2019) - [j19]Werner Dubitzky, Philippe Lopes, Jesse Davis, Daniel Berrar:
The Open International Soccer Database for machine learning. Mach. Learn. 108(1): 9-28 (2019) - [j18]Daniel Berrar, Philippe Lopes, Werner Dubitzky:
Incorporating domain knowledge in machine learning for soccer outcome prediction. Mach. Learn. 108(1): 97-126 (2019) - 2017
- [j17]Daniel P. Berrar, Philippe Lopes, Werner Dubitzky:
Caveats and pitfalls in crowdsourcing research: the case of soccer referee bias. Int. J. Data Sci. Anal. 4(2): 143-151 (2017) - [j16]Daniel Berrar:
Confidence curves: an alternative to null hypothesis significance testing for the comparison of classifiers. Mach. Learn. 106(6): 911-949 (2017) - 2016
- [j15]Daniel Berrar:
Learning from automatically labeled data: case study on click fraud prediction. Knowl. Inf. Syst. 46(2): 477-490 (2016) - 2014
- [j14]Daniel P. Berrar:
An Empirical Evaluation of Ranking Measures With Respect to Robustness to Noise. J. Artif. Intell. Res. 49: 241-267 (2014) - [j13]Richard Jayadi Oentaryo, Ee-Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Minh Nhut Nguyen, Kasun S. Perera, Bijay Neupane, Mustafa Amir Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar:
Detecting click fraud in online advertising: a data mining approach. J. Mach. Learn. Res. 15(1): 99-140 (2014) - 2013
- [j12]Daniel P. Berrar, José Antonio Lozano:
Significance tests or confidence intervals: which are preferable for the comparison of classifiers? J. Exp. Theor. Artif. Intell. 25(2): 189-206 (2013) - [j11]Daniel Peter Berrar, Alfons Schuster:
Computing machinery and creativity: lessons learned from the Turing test. Kybernetes 43(1) (2013) - [j10]Daniel P. Berrar, Akihiko Konagaya, Alfons Schuster:
Turing Test Considered Mostly Harmless. New Gener. Comput. 31(4): 241-263 (2013) - 2012
- [j9]Daniel P. Berrar, Peter A. Flach:
Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them). Briefings Bioinform. 13(1): 83-97 (2012) - 2011
- [j8]Alfons Schuster, Daniel P. Berrar:
The Omnipresent Computing Menace to Information Society. J. Adv. Comput. Intell. Intell. Informatics 15(7): 786-792 (2011) - [j7]Daniel P. Berrar, Georg Ohmayer:
Multidimensional scaling with discrimination coefficients for supervised visualization of high-dimensional data. Neural Comput. Appl. 20(8): 1211-1218 (2011) - 2010
- [j6]Daniel P. Berrar, Naoyuki Sato, Alfons Schuster:
Artificial Intelligence in Neuroscience and Systems Biology: Lessons Learnt, Open Problems, and the Road Ahead. Adv. Artif. Intell. 2010: 578309:1-578309:2 (2010) - [j5]Daniel P. Berrar, Naoyuki Sato, Alfons Schuster:
Quo Vadis, Artificial Intelligence? Adv. Artif. Intell. 2010: 629869:1-629869:12 (2010) - 2006
- [j4]Daniel P. Berrar, Ian Bradbury, Werner Dubitzky:
Avoiding model selection bias in small-sample genomic datasets. Bioinform. 22(10): 1245-1250 (2006) - [j3]Daniel P. Berrar, Ian Bradbury, Werner Dubitzky:
Instance-based concept learning from multiclass DNA microarray data. BMC Bioinform. 7: 73 (2006) - [j2]Jeyakumar Natarajan, Daniel P. Berrar, Werner Dubitzky, Catherine J. Hack, Yonghong Zhang, Catherine DeSesa, James R. Van Brocklyn, Eric G. Bremer:
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. 7: 373 (2006) - 2005
- [j1]Daniel P. Berrar, Brian Sturgeon, Ian Bradbury, C. Stephen Downes, Werner Dubitzky:
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. 12(5): 534-544 (2005)
Conference and Workshop Papers
- 2019
- [c9]Chayut Wiwatcharakoses, Daniel Berrar:
Self-Organizing Incremental Neural Networks for Continual Learning. IJCAI 2019: 6476-6477 - 2017
- [c8]Daniel P. Berrar, Werner Dubitzky:
On the Jeffreys-Lindley Paradox and the Looming Reproducibility Crisis in Machine Learning. DSAA 2017: 334-340 - 2016
- [c7]Daniel Berrar:
On the Noise Resilience of Ranking Measures. ICONIP (2) 2016: 47-55 - 2012
- [c6]Daniel P. Berrar:
Null QQ plots: A simple graphical alternative to significance testing for the comparison of classifiers. ICPR 2012: 1852-1855 - 2006
- [c5]Cândida G. Silva, Vitaliy Ostropytskyy, Nuno Loureiro-Ferreira, Daniel P. Berrar, Martin T. Swain, Werner Dubitzky, Rui M. M. Brito:
P-found: The Protein Folding and Unfolding Simulation Repository. CIBCB 2006: 1-8 - [c4]Daniel P. Berrar, Werner Dubitzky:
Neural Plasma. IFIP AI 2006: 159-168 - 2005
- [c3]Frederic T. Stahl, Daniel P. Berrar, Cândida G. Silva, R. J. Rodrigues, Rui M. M. Brito, Werner Dubitzky:
Grid warehousing of molecular dynamics protein unfolding data. CCGRID 2005: 496-503 - 2003
- [c2]Daniel P. Berrar, C. Stephen Downes, Werner Dubitzky:
A Probabilistic Neural Network for Gene Selection and Classification of Microarray Data. IC-AI 2003: 342-352 - [c1]Daniel P. Berrar, C. Stephen Downes, Werner Dubitzky:
Multiclass Cancer Classification Using Gene Expression Profiling and Probabilistic Neural Networks. Pacific Symposium on Biocomputing 2003: 5-16
Editorship
- 2014
- [e2]Huiru Jane Zheng, Werner Dubitzky, Xiaohua Hu, Jin-Kao Hao, Daniel P. Berrar, Kwang-Hyun Cho, Yadong Wang, David R. Gilbert:
2014 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2014, Belfast, United Kingdom, November 2-5, 2014. IEEE Computer Society 2014, ISBN 978-1-4799-5669-2 [contents] - 2006
- [e1]Eric G. Bremer, Jörg Hakenberg, Eui-Hong Han, Daniel P. Berrar, Werner Dubitzky:
Knowledge Discovery in Life Science Literature, PAKDD 2006 International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings. Lecture Notes in Computer Science 3886, Springer 2006, ISBN 3-540-32809-2 [contents]
Reference Works
- 2019
- [r4]Daniel Berrar:
Bayes' Theorem and Naive Bayes Classifier. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 403-412 - [r3]Daniel Berrar:
Cross-Validation. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 542-545 - [r2]Daniel Berrar:
Performance Measures for Binary Classification. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 546-560 - [r1]Daniel Berrar:
Introduction to the Non-Parametric Bootstrap. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 766-773
Coauthor Index
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