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We selected AO classification to classify fractures in our series based on these observations.
Michielan et al. [20] employed multi-label multi-class classification to classify cytochrome p450 substrates.
Happy et al. [43] suggest the use of salient patches with discriminative features and use one-against-one classification to classify pairs of expressions.
Here we use a machine learning approach, Support Vector Machine (SVM) classification, to classify 10,085 building roofs in relation to their received solar energy in the city of Geneva in Switzerland.
Tracker [84] uses a region-based stereo algorithm to find 3D points inside an object, and Bayesian Classification to classify each pixel as belonging to a person or the background.
We also used principal component analysis and K-nearest neighbor's classification to classify the samples, using the default setting in MeV.
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Analogously, we used ATC Anatomical Main Group classifications to classify drugs.
In this section, we firstly introduce a classification algorithm to classify the task activations (jobs) in mandatory or optional.
Our aim in this article is to verify that SVM can be used as a powerful classification technique to classify the quality of DNA chromatograms.
We, therefore, reduce the features from 41 to 13 and use J.4.8, a version of C4.5 decision tree classification algorithm to classify data as either normal or anomaly.
It provides an academic database of literature between the periods of 1973– 2014 covering 69 journals and proposes a classification scheme to classify the articles.
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