This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of linearly ordered features, as one...
Cheng and Church proposed a greedy deletion-addition algorithm to find a given number of k biclusters, whose mean squared residues (MSRs) are below certain thresholds and the miss...
Stefan Gremalschi, Gulsah Altun, Irina Astrovskaya...
: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of...
Janez Brank, Dunja Mladenic, Marko Grobelnik, Nata...