Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
We present a comparative evaluation of two data-driven models used in translation selection of English-Korean machine translation. Latent semantic analysis(LSA) and probabilistic ...
Algorithm portfolios aim to increase the robustness of our ability to solve problems efficiently. While recently proposed algorithm selection methods come ever closer to identifyin...
Serdar Kadioglu, Yuri Malitsky, Ashish Sabharwal, ...
An experimental study on two decision issues for wrapper feature selection (FS) with multilayer perceptrons and the sequential backward selection (SBS) procedure is presented. The ...
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...