Daniel P. Berrar

According to our database1, Daniel P. Berrar authored at least 35 papers between 2003 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2020
SOINN+, a Self-Organizing Incremental Neural Network for Unsupervised Learning from Noisy Data Streams.
Expert Syst. Appl., 2020

2019
Introduction to the Non-Parametric Bootstrap.
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019

Performance Measures for Binary Classification.
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019

Cross-Validation.
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019

Bayes' Theorem and Naive Bayes Classifier.
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 1, 2019

The Open International Soccer Database for machine learning.
Mach. Learn., 2019

Guest editorial: special issue on machine learning for soccer.
Mach. Learn., 2019

Incorporating domain knowledge in machine learning for soccer outcome prediction.
Mach. Learn., 2019

Should significance testing be abandoned in machine learning?
Int. J. Data Sci. Anal., 2019

Self-Organizing Incremental Neural Networks for Continual Learning.
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

Caveats and pitfalls in crowdsourcing research: the case of soccer referee bias.
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
Learning from automatically labeled data: case study on click fraud prediction.
Knowl. Inf. Syst., 2016

On the Noise Resilience of Ranking Measures.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

2014
Detecting click fraud in online advertising: a data mining approach.
J. Mach. Learn. Res., 2014

An Empirical Evaluation of Ranking Measures With Respect to Robustness to Noise.
J. Artif. Intell. Res., 2014

2013
Turing Test Considered Mostly Harmless.
New Gener. Comput., 2013

Computing machinery and creativity: lessons learned from the Turing test.
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

The Omnipresent Computing Menace to Information Society.
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

Quo Vadis, Artificial Intelligence?
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

Instance-based concept learning from multiclass DNA microarray data.
BMC Bioinform., 2006

Avoiding model selection bias in small-sample genomic datasets.
Bioinform., 2006

Neural Plasma.
Proceedings of the Artificial Intelligence in Theory and Practice, 2006

P-found: The Protein Folding and Unfolding Simulation Repository.
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

Grid warehousing of molecular dynamics protein unfolding data.
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


  Loading...