Soft combination of neural classifiers: a comparative study
Pattern Recognition Letters
A Theoretical Study on Six Classifier Fusion Strategies
IEEE Transactions on Pattern Analysis and Machine Intelligence
On combining classifiers using sum and product rules
Pattern Recognition Letters
Ensembling neural networks: many could be better than all
Artificial Intelligence
Evolving Teams of Predictors with Linear Genetic Programming
Genetic Programming and Evolvable Machines
An Empirical Study of Multipopulation Genetic Programming
Genetic Programming and Evolvable Machines
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Characteristic attributes in cancer microarrays
Journal of Biomedical Informatics
Cancer classification using gene expression data
Information Systems - Special issue: Data management in bioinformatics
Behavioral Diversity and a Probabilistically Optimal GP Ensemble
Genetic Programming and Evolvable Machines
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Artificial Intelligence Review
Genetic Programming for Mining DNA Chip Data from Cancer Patients
Genetic Programming and Evolvable Machines
Multistrategy Ensemble Learning: Reducing Error by Combining Ensemble Learning Techniques
IEEE Transactions on Knowledge and Data Engineering
Genetic programming in classifying large-scale data: an ensemble method
Information Sciences: an International Journal - Special issue: Soft computing data mining
Comprehensive vertical sample-based KNN/LSVM classification for gene expression analysis
Journal of Biomedical Informatics - Special issue: Biomedical machine learning
Cancer classification and prediction using logistic regression with Bayesian gene selection
Journal of Biomedical Informatics - Special issue: Biomedical machine learning
A primer on gene expression and microarrays for machine learning researchers
Journal of Biomedical Informatics - Special issue: Biomedical machine learning
Diversity in genetic programming: an analysis of measures and correlation with fitness
IEEE Transactions on Evolutionary Computation
Artificial Intelligence in Medicine
An Epicurean learning approach to gene-expression data classification
Artificial Intelligence in Medicine
A constructive algorithm for training cooperative neural network ensembles
IEEE Transactions on Neural Networks
Population variation in genetic programming
Information Sciences: an International Journal
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
A novel ensemble of classifiers for microarray data classification
Applied Soft Computing
A GP Based Approach to the Classification of Multiclass Microarray Datasets
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Dynamic population variation in genetic programming
Information Sciences: an International Journal
Artificial Intelligence in Medicine
Microarray data classification based on ensemble independent component selection
Computers in Biology and Medicine
Classification of oncologic data with genetic programming
Journal of Artificial Evolution and Applications - Special issue on artificial evolution methods in the biological and biomedical sciences
Predicting protein subcellular locations for Gram-negative bacteria using neural networks ensemble
CIBCB'09 Proceedings of the 6th Annual IEEE conference on Computational Intelligence in Bioinformatics and Computational Biology
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Ensemble approaches of support vector machines for multiclass classification
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Ensemble gene selection for cancer classification
Pattern Recognition
Artificial Intelligence in Medicine
On the use of genetic programming for the prediction of survival in cancer
Proceedings of the 12th annual conference on Genetic and evolutionary computation
EvoBIO'10 Proceedings of the 8th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Gene expression profiling using flexible neural trees
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Expert Systems with Applications: An International Journal
Understanding physiological responses to stressors during physical activity
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
A fuzzy evolutionary framework for combining ensembles
Applied Soft Computing
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Object: The classification of cancer based on gene expression data is one of the most important procedures in bioinformatics. In order to obtain highly accurate results, ensemble approaches have been applied when classifying DNA microarray data. Diversity is very important in these ensemble approaches, but it is difficult to apply conventional diversity measures when there are only a few training samples available. Key issues that need to be addressed under such circumstances are the development of a new ensemble approach that can enhance the successful classification of these datasets. Materials and methods: An effective ensemble approach that does use diversity in genetic programming is proposed. This diversity is measured by comparing the structure of the classification rules instead of output-based diversity estimating. Results: Experiments performed on common gene expression datasets (such as lymphoma cancer dataset, lung cancer dataset and ovarian cancer dataset) demonstrate the performance of the proposed method in relation to the conventional approaches. Conclusion: Diversity measured by comparing the structure of the classification rules obtained by genetic programming is useful to improve the performance of the ensemble classifier.