Sentence examples for class and classification from inspiring English sources

Centers for Disease Control and Prevention CDCC) definition for wound class and classification of SSI were used.

Fadi et al. [81] presented an automated system to identify space occupying lesions on the brain using EEG signals where EEG features were extracted using wavelet transform for different tumour classes and classification by self-organising maps.

For this purpose memory was trained on the learning sample in order to form attractors. Then attractors were assigned to classes, and classification rate was measured on an independent test sample.

One of these studies [ 8] used motifs to analyze human and mouse OR repertoires, focusing on classification of the motifs into classes and classification of the ORs using these motifs as features.

In this section we describe the applicability of several of the KR formalisms underlying ontology technology to structure-based class definition and classification, highlighting the capabilities and limitations of each formalism.

Thus, both direct concatenation and SNF can clearly identify the true patient relationships and demonstrate good performance for both class discovery and classification.

We evaluated the factors that may affect integration of different types of datasets for disease class discovery and classification by simulation.

The iBFE method is motivated by the observation that the accuracy of disease class discovery and classification can be significantly improved in the feature space extracted from the original data [ 18– 20].

In Tables 4 and 5, the number of training and test samples of each class and the classification accuracies for these data sets are given.

Inspired by taxonomic best practices, the tentative classification system described in this paper proposes that each EPA on PsychTable be assigned a three-letter symbol, a functional class, and a classification number, similar to the Periodic Table of the Elements.

The key contribution of this work is the idea that global structural information of human activities can be encoded using a subset of their local event subsequences, and that this encoding is sufficient for activity-class discovery and classification.