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In order to eliminate the influence of unavoidable outliers in training sample on a model's performance, a novel least square support vector machine regression, which combines outlier detection approach and adaptive weight value for the training sample, is proposed and named as adaptive weighted least square support vector machine regression (AWLS-SVM).
where α and β are the weight value for LET and link availability probability, respectively.
Open image in new window Fig. 1 Weight Value for Criteria and Indicators Degree of Injury Using AHP.
A single weight value for each ConfiguredService is computed, and the services are ranked based on these weights.
It is hypothesized that a higher weight value for a pair of interacting proteins denotes there would be more flow.
The interface can be used also to identify neurons which have for example large or small weight value for certain descriptor or response.
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First, the weight values for every behavior are determined.
Normalized relative spending (NRS) is adapted to normalize the weight values for the inference engine.
The UE throughput value is also utilized to determine individual UE weight values for proportional fairness.
The optimal weight values for the Weighted SUM rule were empirically determined.
where the weight values for each direction are calculated by using Eq. (12).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com