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The added value of the RATA approach was illustrated in the sample discrimination for some food products when using the weighted attribute scores for analysis.
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Then they were optimized using the weighted property index method.
Typically the additive value function is assessed using the weighted summation approach: single-attribute value functions are separately assessed, then attribute scaling constants are assessed to weight and combine the single-attribute functions.
Finally, an evaluating node computes the final trust of an evaluated node in the context of all the trust attributes using the weighted sum.
SMI attribute scores are calculated using the weighted sum model of relevant measures.
Using the weighted equivalent of degree, a weighted counterpart to leverage centrality can then be calculated at each node.
The degree of agreement was analyzed using the weighted κ.
The data were transformed using the weighted least squares method.
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Expression was assessed using the weighted histoscore method.
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