The goal of this paper is to improve the prediction performance of fault-prone module prediction models (fault-proneness models) by employing over/under sampling methods, which ar...
Within the taxonomy of feature extraction methods, recently the Wrapper approaches lost some popularity due to the associated computational burden, compared to Embedded or Filter m...
Erik Schaffernicht, Volker Stephan, Horst-Michael ...
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...