Sentence examples for model to generalize from inspiring English sources
Generally, the ability of a model to generalize to new populations and nominally unrelated individuals will depend on the trait architecture; for a finite, relatively small, number of training samples, the larger and fewer the genetic effects associated with a trait the easier it will be for a model to separate this predictive signal from other data structure.
Jet characteristic equations were introduced in the model to generalize its application to mechanically ventilated buildings.
Models can be rerun on new test sets, either to get tighter confidence bounds on model performance, or to evaluate the ability of the model to generalize to new domains.
The modified parameters were estimated for the collector field based on measurement and the data were used in the model to generalize the results for field with different piping to collector area ratios.
In order for the PLSA model to generalize well on "new" (unseen) documents, Hofmann [54, 55] proposed a modified EM algorithm for PLSA called TEM algorithm.
Figure 1a shows a complex diagram of IPD error model to generalize the conventional model to all possible DOA angle range.
Critiques of connectionist models of language often center on the inability of these models to generalize symbolically (Fodor & Pylyshyn, 1988; Marcus, 1998).
The experiments show that the approach can use multiple models to generalize to new objects in that it outperforms grasping based on the closest model.
The purported inability of connectionist models to generalize performance in this way has become an important theme in the systematicity debate.
Beyond previous investigations [22], this article also assesses the ability of the considered echo path models to generalize for double-talk situations, in which the models cannot be adapted to the current input signal.
Since the testing process simulates the capability of the models to generalize on new and never-seen-before cases, we focus on the testing performance of the models in the presentation and analysis of the results.
