• Publications
  • Influence
Classifier selection for majority voting
Abstract Individual classification models are recently challenged by combined pattern recognition systems, which often show better performance. In such systems the optimal set of classifiers is firstExpand
  • 454
  • 27
  • Open Access
An Overview of Classifier Fusion Methods
A number of classifier fusion methods have been recently developed opening an alternative approach leading to a potential improvement in the classification performance. As there is little theory ofExpand
  • 350
  • 13
  • Open Access
Big education: Opportunities for Big Data analytics
  • Ling Cen, D. Ruta, J. Ng
  • Computer Science
  • IEEE International Conference on Digital Signal…
  • 21 July 2015
Big Data have demonstrated significant values in extension of our insight and foresight into the world. With the rapid development of communication technologies and mobile devices, educational dataExpand
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  • 6
Churn Prediction: Does Technology Matter?
The aim of this paper is to identify the most suitable model for churn prediction based on three different techniques. The paper identifies the variables that affect churn in reverence of customerExpand
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Genetic algorithms in classifier fusion
An intense research around classifier fusion in recent years revealed that combining performance strongly depends on careful selection of classifiers to be combined. Classifier performance depends,Expand
  • 109
  • 4
Quantitative approach to collaborative learning: performance prediction, individual assessment, and group composition
The benefits of collaborative learning, although widely reported, lack the quantitative rigor and detailed insight into the dynamics of interactions within the group, while individual contributionsExpand
  • 30
  • 4
Analysis of the Correlation Between Majority Voting Error and the Diversity Measures in Multiple Classifier Systems
Combining classifiers by majority voting (MV) has recently emerged as an effective way of improving performance of individual classifiers. However, the usefulness of applying MV is not alwaysExpand
  • 70
  • 3
  • Open Access
Physical field models for pattern classification
Recent findings in pattern recognition show that dramatic improvement of the recognition rate can be obtained by application of fusion systems utilizing many different and diverse classifiers for theExpand
  • 9
  • 3
Application of the Evolutionary Algorithms for Classifier Selection in Multiple Classifier Systems with Majority Voting
In many pattern recognition tasks, an approach based on combining classifiers has shown a significant potential gain in comparison to the performance of an individual best classifier. ThisExpand
  • 49
  • 2
  • Open Access
Automated Trading with Machine Learning on Big Data
  • D. Ruta
  • Computer Science
  • IEEE International Congress on Big Data
  • 27 June 2014
Financial markets are now extremely efficient,nevertheless there are still many investment funds that generatealpha systematically beating markets' return benchmarks. Theemergence of big data gaveExpand
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  • 2