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The most relevant molecular descriptors were selected using the genetic algorithm as a feature selection tool.
Then a feature selection is used in the learning process to select the most useful features to train a classifier.
A feature selection method based on sensitivity analysis was carried out to select superior features.
A feature selection algorithm is proposed to deal with the high dimensionality and select discriminant fluorescence wavelengths.
In this work, we propose a feature selection framework for constructing an occupancy estimator.
The system was optimized by eliminating unimportant features using a feature selection method (UTA method).
A feature selection method designed specifically for SVMs is presented in (Weston et al. citeyearweston).
In this paper, a feature selection algorithm based on synonym merging named SM-CHI is proposed.
This work presents a feature selection method based on ABC algorithm.
NoConstant90 has been used coupled with a feature selection algorithm (for example BestFirst).
First, a subset of available features is identified using a feature selection algorithm.
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