The problem of selecting a sample subset sufficient to preserve diversity arises in many applications. One example is in the design of recombinant inbred lines (RIL) for genetic a...
Feng Pan, Adam Roberts, Leonard McMillan, David Th...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Abstract— Scheme-specific attribute selection with the wrapper and variants of forward selection is a popular attribute selection technique for classification that yields good ...
Martin Gutlein, Eibe Frank, Mark Hall, Andreas Kar...
Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...