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The neural network however has a simpler model training procedure, boarder choice of training data, and smaller computational cost.
The choice of training data set has an impact on the outcome of the emotions.
However, as will be pointed out in the paper, the choice of training data is straightforward.
Note that the choice of training data sets to establish the random forest is crucial.
Third, the quadratic model is more robust to the choice of training data, indicating that it describes the regulatory relationship uniformly across the embryo: the model performs consistently whether it is trained on either of the two stripes, a restricted region around the lateral midline, or only on the stripes and their immediately neighboring nuclei.
Further, a marginal gain of 0.0002 could have been obtained in the final summation of scores by transforming the NN output using the logistic function centered on 0.5, but this gain is not consistent with the choice of training data used in the NN (P, P+GE or Rat P).
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The selection of training data is critical.
It is desirable to evaluate system accuracy by comparing the FAR to the FRR for different choices in angular range of training data.
Let us now analyze different factors influencing the ASR back-end such as the number of hidden layers and the size of the input context, the influence of training data, and the choice of adaptation strategy.
The high accuracy achieved by the proposed method may be attributed to (1) better design philosophy of classifiers; (2) good choice for the feature vectors; (3) accurate labeling of training data; and (4) exploitation of experts' knowledge.
The optimality of the MLE training criterion is conditioned on the availability of an infinite amount of training data and the correct choice of the model.
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