Sentence examples for discarded features from inspiring English sources

We show the number of features selected by each algorithm in Tables 6 and 7, which also lists the number of discarded features, input features, and target features.

Furthermore, the ratio of the number of input features to the number of output features for GA-MTL is similar to the ratio of the number of input features to the number of discarded features for GA-FS.

The basic idea is to use the selected features as the input feature set and to combine the target values with some of the discarded features to form the target output.

(3) For e-GA-MTL, although the number of input, output and discarded features are determined automatically by the genetic algorithm, the ratios among these numbers are similar to those for H-MTL and GA-MTL-IR.

(2) H-MTL and GA-MTL-IR both use the same prediction risk criterion to discard irrelevant features, so the features discarded are the same and hence the number of discarded features are the same.

If so, the discarded feature was included again in the subset, and otherwise definitely eliminated from the pool.

Multi-Task Learning (MTL) is a method of using the redundant information by selecting features from the discarded feature set to add to the target [ 8, 9].

The system is able to discard features that are not extremely necessary for the tasks, thus, reducing the processing time.

Results demonstrate that discarding features that are more prone to distortions allows lighter processing, but also produces better performance than using the full set of features.

Aggregating feature counts provided adequate feature density and reduced the dimensionality without discarding features that could be informative.

Additionally the percentage of instances of a given phenotype can also be used to discard features that are likely to be irrelevant.