Sentence examples similar to labeled learning approaches from inspiring English sources

As a matter of fact, the multi-label learning approach appears to be a good candidate for modeling overlapped medical conditions, specific to chronically ill patients.

In the experiment of 10 text classification tasks, it was shown that RDE-based semi-supervised learning improved the AUC performance by over 10% against SVM, logistic regression and some other classical semi-supervised learning approaches; using 5000 labeled examples plus 13 million unlabeled ones the performance of the new method was close to the result of 13 million labeled examples.

Our code also allows users to implement supervised learning approaches with their own representative labeled training data.

Active learning approaches [13, 33, 36] reduce label complexity by analyzing unlabeled instances and selecting the most useful ones once labeled.

Both the Marszalek [73] and Song [110] approaches are not transfer learning approaches and are trained on the limited labeled target data.

In addition, we discuss on the consistency of learning approaches that address multi-label learning by decomposing into a set of binary classification problems.

Our results prompt a consideration of the current status of established approaches to patent landscaping, such as key-word or technology classifications and other approaches relying on semantic labelling, in the context of novel machine learning approaches.

Traditional supervised learning approaches primarily work in the single-label environment.

After determination of compound overlap, machine learning approaches were used to establish multi-label classification models for BCRP/P-gp.

Traditional machine learning approaches to genome annotation typically rely on large amounts of labeled data.

Machine learning approaches that model only the distribution of a label when given the features.