Sentence examples for classification of instances from inspiring English sources
The prediction is done as classification of instances into coarse lower or higher-than-average classes.
These algorithms generate decision trees by forming them top to down and identify the prime attribute that is to be chosen for classification of instances in a given dataset (i.e. it is in accordance with the selected target attribute).
Classification of instances is based upon aggregate voting over all trees in the forest.
Furthermore, at level 1, the combination of parameters that was selected most often for the k = 10 test folds, i.e. mode of the selected combinations, was used for final classification of instances in the outermost test fold.
Unlike traditional tree models obtained from algorithms such as C4.5, the classification of instances by ADtree is thus not determined by a single path traversed in the tree but rather by a collection of paths.
Bayesian networks model conditional dependencies among the domain variables, and provide a way to deduce their interrelationships as well as a method for the classification of new instances.
The resulting network together with the Bayes optimal classifier is used for classification of new instances.
After the construction of the KAOG network, a Bayes optimal classifier (BayesOC) performs the classification of new instances using the constructed network.
The presence of missed events will likely diminish accuracy of classification (for instance, because individuals who actually experienced an event but were admitted elsewhere are mislabeled), although we cannot exclude the possibility that some apparent predictors of lower risk actually predict failure to follow-up within these health systems.
The main barrier was the proper curation of the generic reactions and the classifications of lipid instances, such that generic reactions were instantiated correctly.
The data elements of the classification are instances of the precancer domain and the properties of the domain instances.
