Sentence examples for embedded techniques from inspiring English sources

Embedded techniques achieve an interaction between the channel selection and the classification.

Approaches to feature selection are generally categorized into filter, wrapper, and embedded techniques.

In the embedded techniques, the channels are selected based on criteria generated during the learning process of a specific classifier because the selection is included into the classifier construction [9].

Embedded techniques are defined for a specific classification method.

Filter approach does not interact with the classifier, contrarily to wrapper and embedded techniques, usually resulting in lower performance.

The multivariate feature selection approaches can be broadly divided into the following categories: (1) filter techniques (e.g., fast correlation-based algorithm [ 11]), (2) wrapper techniques (e.g., GA/KNN method (combining a Genetic Algorithm (GA) and the k-Nearest Neighbor (KNN) method) [ 12]), and (3) embedded techniques (e.g., random forest [ 13]).

These policies are implemented in the simulation model by using the embedded technique.

There are two commonly used embedding techniques.

We employ the Tanimoto similarity measure for the clustering and embedding techniques.

The distortion and rate calculations for the R-D block and the embedding techniques are explained in the following subsections.

Besides, embedding techniques have shown potential in handling categorical inputs, which can enhance the overall performance of forecasting.