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PNN was implemented in Classification Toolbox for use with MATLAB [82].
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Because of the great complexity associated with the problem, two machine learning techniques, Support Vector Machines (SVM) and Support Vector Machines trained with Sequential Minimal Optimization (SMO), are implemented in developing model classification.
This was performed using SVMs implemented in the LIBSVM classification library (Platt, 1999; Chang and Lin, 2011).
Random forest classification, implemented in boruta, was used to identify taxa or CAZymes predictive of total 13C incorporation into DNA or PLFA.
Remarkably, using the non-redundant functional classification implemented in MapMan software we were able to identify several pathways that showed coordinated changes in gene expression that was restricted to only one of the parental genomes.
Starting with the MicroCyc or KEGG data, the user can choose from two up to fifteen organisms and select a subset or all the metabolic pathways from the classification implemented in KEGG or MetaCyc (39) (top of Figure 2D).
To gain insight into the predicted functional characteristics of the current dataset, translated products were functionally annotated using the Gene Ontology (GO) classification as implemented in the Blast2GO software [ 34], as well as using the InterPro classification [ 35].
The decision tree algorithm implemented in scikit-learn is CART (Classification and Regression Trees).
Some papers have been published with reported research work mainly on defect classification aspects implemented in commercially procured systems.
The application of wine quality classification is implemented in Zhang [141] using a multi-task transfer learning approach.
We compared the accuracy of the prediction by using the different classification methods implemented in BRB-Array tools.
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