Floating search method

SVM-BFS — Application of Wrapper Method and Floating Search Method... 

Floating search method proposed by Pudil et al. [112] is used as feature subset generation procedure, and has been proved to be one of the best subset generation algorithms for moderately large or small data sets. Backward floating search (BFS) method needs more computer time than forward floating search method, but it can treat interactive features well, so we combine it with SVM based on wrapper method and name it SVM-BFS method. 

Pudil, P., Novovicova, J. and Kittler, J. (1994). Floating search methods in feature selection. Pattern recognition letters, IS, pp. 1119-1125. 

Pudil, P., Novovicov, J., Kittier, J. Floating Search Methods in Feature Selection. Pattern Recognition Letters 15,1119-1125 (1994)... 

A SVC-based feature selection method is applied for descriptor selection. Using floating search technique, the subset of descriptors is selected out via LOO cross-validation. By this way, three descriptors, Cn (charge density of the atom N connecting with R), Dipole (dipole moment) and Hf (heat of formation) are selected for modeling use. Table 9.4 lists the samples with bioactivities MIC and selected descriptors. 

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