Sentence examples for size for classification from inspiring English sources

Computational Intelligence techniques have the potential to provide powerful tools for addressing these challenges, but the current literature focuses mainly on handling scalability issues related to data volume in terms of sample size for classification tasks.

However, Breiman et al.[25] have found in the case of selecting optimal tree size for classification tree models that the tree size with minimal cross-validation error generates a model which generally overfits.

After training the SVM, we formatted all overlapping 10 kb windows (100 bp step size) for classification, and rescaled these windows using the same scalars used for the training set.

In the original MMG model, the GOP size boundaries for classification are geometrically separated.

A review of literature on the subject of using DEAP datasets reported that the best emotion classification results could be obtained by using a sliding window size of 3 s for arousal classification and 6 s window size for valence classification in the feature extraction process [25].

A priori power was not obtained in the study because of a decrease in the overall sample size and the realization of a third patient classification (new diabetes), which further limited the sample size for each classification group.

It is also necessary to check the classification accuracy for various window sizes and optimize the window size for best classification.

52 58 There is a dependency on disc size for MRA and GPS classification.

Among the 353 datasets, both studies of Lindner et al. [ 17] and Kuo et al. [ 18] provided comprehensive information of patients' pathological stage of TNBC as well as sufficient sample sizes for our classification rule and matched our goal to search for common pathways on different races.

Accordingly, they would not have been identified if both OMR and pupillary size analysis were required for classification.

Detection of plasma membrane Y1 YFP fluorescence was minimized because of the size and intensity constraints for classification.