Selecting the best features in a dataset improves accuracy and efficiency of classifiers in a
learning process. Datasets generally have more features than necessary, some of them …

There are some problems in the distribution system such as, real power losses, lagging
components of the current circuit that happened due to the growth of the load. These …

Variable Selection in large datasets is a commonly procedure in multivariate calibration,
which is a field of study from chemometrics. Selecting the most informative variables …

Variable selection is an important procedure to select relevant features from large datasets
in optimization problems. The use of epistasis concepts becomes an alternative to assess …

Variable selection is the procedure used to choose a subset of suitable features contained in
a given dataset. Selecting variables becomes important when the dataset contains many …