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Adaptive network structure is employed to minimize classification error.
The optimum rank was selected to minimize classification error of the cross-validated samples and was determined to be 3 latent variables.
Since the gait data are not linearly separable in this study, in order to minimize classification error, some nonnegative slack variables (ξ i ≥ 0 is a measure of misclassification errors) and a penalty function F γ = ∑ i ξ i γ γ ≥ 0 are employed in SVM classification algorithm.
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In the classification task, whether it is to lessen the computation time, or to minimize classification errors, any method may be chosen based on its efficiency and ability to complete the task as required.
The combination of the answers given to the respective question was necessary in order to minimize classification errors.
In addition, patients with PD were identified using both ICD-9-CM diagnostic codes and PD treatment codes in this study to minimize classification errors.
This method takes the prior methylation distribution into account to infer methylation status in the framework of Bayesian probabilistic models, which is known to minimize classification errors in the presence of a known alternative hypothesis [ 18].
An optimal linear classifier then can be found by minimizing classification error (probability of misclassification).
The optimal weights for this speaker identification scheme can be obtained by using the MCE-based discriminative training algorithm [5, 12, 14 16], which aims at deriving a set of speaker models which minimizes classification errors, that is, speaker identification errors for training data.
Bayesian classifier minimizes classification error.
The abstract representation allows for faster and safer comparisons of similarities between images because the discrete domain of features minimizes classification errors.
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CEO of Professional Science Editing for Scientists @ prosciediting.com