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Dataset complexity can help to generate accurate ensembles of k-nearest neighbors
2008
2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)
Gene expression based cancer classification using classifier ensembles is the main focus of this work. A new ensemble method is proposed that combines predictions of a small number of k-nearest neighbor (k-NN) classifiers with majority vote. Diversity of predictions is guaranteed by assigning a separate feature subset, randomly sampled from the original set of features, to each classifier. Accuracy of k-NNs is ensured by the statistically confirmed dependence between dataset complexity,
doi:10.1109/ijcnn.2008.4633831
dblp:conf/ijcnn/OkunV08
fatcat:mcttmo5inbcdbhibfchzhbhv3u