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WWW
2005
ACM
14 years 10 months ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
Yan-Shi Dong, Ke-Song Han
IJCNN
2000
IEEE
14 years 2 months ago
Unsupervised Learning of Neural Network Ensembles for Image Classification
In the field of pattern recognition, the combination of an ensemble of neural networks has been proposed as an approach to the development of high performance image classification...
Giorgio Giacinto, Fabio Roli, Giorgio Fumera
SIGMOD
2010
ACM
196views Database» more  SIGMOD 2010»
13 years 10 months ago
GAIA: graph classification using evolutionary computation
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...
Ning Jin, Calvin Young, Wei Wang
GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
13 years 11 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
KDD
2002
ACM
126views Data Mining» more  KDD 2002»
14 years 10 months ago
Integrating feature and instance selection for text classification
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Dimitris Fragoudis, Dimitris Meretakis, Spiros Lik...