Sentence examples for many feature selection from inspiring English sources

As an information theoretic criteria, MI have been applied in many feature selection problems [25].

However many feature selection methods are mainly designed for incomplete data with categorical features.

To address this issue, many feature selection algorithms have been proposed, however, these algorithms are often computationally time-consuming.

As a result, a large number of combinations is possible; hence, many feature selection techniques have been proposed throughout the time, and below are some of them.

Many feature selection methods used for dealing with this problem are focused on statistical relationships among the descriptors and target properties, leaving aspects associated with the chemical knowledge out of the picture.

The greedy subset selection scheme was motivated by a similar approach successfully being used in many feature selection problems [17].

Although many feature selections have taken both feature relevance and redundancy into account simultaneously for predictability [11], they neglect stability [12].

Also, we use a freely available toolbox called Weka [10] where many feature-selection algorithms are available.

High feature correlation impedes many feature-selection techniques.

Also, the resulting discretized dimensions can be coupled with many effective feature selection approaches found in the literature.

Finding an optimal feature subset for a problem in an outsized domain becomes intractable and many such feature selection problems have been shown to be NP-hard.