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The classification clusters repeats according to the features within the specific mask, but averaging was always carried out using the entire repeat.
Functional classification – Clusters were assigned putative functional categorization using two methods.
Informational genes in each genome were identified by applying the COG classification (Clusters of Orthologous Groups of proteins) [ 66].
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and classification (clustering).
They cover classification, clustering, regression, association analysis, and network analysis.
The solution is useful to solve data classification, clustering, and dimensionality reduction problems.
Support vector machines (SVMs) are a widely used technique for classification, clustering and data analysis.
It provides classification, clustering and association rule mining methods that are common to many data mining systems.
Artificial neural networks (ANN), have shown to be an effective, general-purpose approach for pattern recognition, classification, clustering, and prediction.
Discrimination, Classification, Clustering deal with dividing a data matrix into two or more groups of measurements (objects).
This involves data mining methods such as "classification," "clustering," or network analysis to identify "patterns of interest" [75 77].
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