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The system was optimized by eliminating unimportant features using a feature selection method (UTA method).
Second, the form features needing to be suppressed are extracted using a feature recognition method with user defined feature facility based on the region-level representation, establishing the feature-level representation.
First, a subset of available features is identified using a feature selection algorithm.
To evaluate our machine learning framework, we firstly run experiments using a feature selection step (Recursive Feature Elimination (RFE) [16]).
You can get recommendations from your friends using a feature called Nook friends, although this feature is somewhat muted in this version of the Nook software.
where AB shape is the common shape volume between the conformer pair (using a precomputed shape-grid at 0.25 Å resolution) and AB feature is the sum of six component feature overlaps (using a feature atom radius of 1.25 Å, to account for proximate color atoms).
This method utilizes kernel matching techniques to map target instances to the source rather than using a feature-based feature transformation.
To find the set of the most important features, we started a large-scale feature selection using a correlation-based feature selection (CFS) approach (Hall, 2000).
This paper presents an approach for configuring RBAC features using a combination of feature modeling and UML modeling.
We reduced set of features using a greedy backward feature elimination and AIC as a model performance measure.
In our algorithm, as it is the case in most appearance-based approaches, we will need to use a feature extraction algorithm to find those features that best describe and discriminate among face images of distinct people.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com