Solving Complex Machine Learning problems with Ensemble Methods

Anomaly Detection by Bagging
Tomas Pevny
Prototype Support Vector Machines: Supervised Classification in Complex Datasets
April Shen and Andrea Danyluk
Local Neighbourhood in Generalizing Bagging for Imbalanced Data
Jerzy Błaszczyński, Jerzy Stefanowski and Marcin Szajek
An Ensemble Approach to Combining Expert Opinions
Hua Zhang, Evgueni Smirnov, Nikolay Nikolaev, Georgi Nalbantov and Ralf Peeters
An Empirical Comparison of Supervised Ensemble Learning Approaches
Mohamed Bibimoune, Haytham Elghazel and Alex Aussem
Clustering Ensemble on Reduced Search Spaces
Sandro Vega-Pons and Paolo Avesani
Software Reliability prediction via two different implementations of Bayesian model averaging
Alex Sarishvili and Gerrit Hanselmann
Multi-Space Learning for Image Classification Using AdaBoost and Markov Random Fields
Wenrong Zeng, Xue-Wen Chen, Hong Cheng and Jing Hua
Efficient semi-supervised feature selection by an ensemble approach
Mohammed Hindawi, Haytham Elghazel and Khalid Benabdeslem
Identification of Statistically Significant Features from Random Forests
Jérôme Paul, Michel Verleysen and Pierre Dupont
Feature ranking for multi-label classification using predictive clustering trees
Dragi Kocev, Ivica Slavkov and Sašo Džeroski

Comments are closed.