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The predicted activity for a given compound corresponds to the weighted sum (using the optimized model weight vector) of the predictions generated by the individual models.
As in the standard model, weight is related to prices.
For ANN model, weight analysis is carried out to analyze the role of various descriptors in activity prediction.
We provide a novel argument that significance testing must be employed when evaluating model reliability, and introduce an evaluation approach that accounts for both the overall activity and spatial structure of a model, substantially affecting reliability estimation and showing that model weight smoothing can improve reliability.
Coefficients p A, p L, and p I are the acoustic model weight, the language model weight, and the word insertion penalty, respectively.
Information about the vehicles involved contains make and model, weight, registration date, maneuvers, and collision point.
Usually, we set the acoustic model weight to 1 and we use an optimization algorithm for the remaining weights.
During decoding, no attempt was made to fine-tune the language model weight and the phone insertion penalty parameters; they were just set to 1.0 and 0.0, respectively.
We perform several recognition run-throughs on the development set to find the best language model weight and word insertion penalty for the first recognition pass.
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Weigel, A. P., Knutti, R., Liniger, M. & Appenzeller, C. Risks of model weighting in multimodel climate projections.
And our forecast model weights the economic factors less and less as time goes on.
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