learning, multi-label classification or multi-output classification is a variant of the classification problem where multiple nonexclusive labels may be...

variety of strategies. Multiclass classification should not be confused with multi-label classification, where multiple labels are to be predicted for each...

inference Classification rule Confusion matrix Detection theory Kernel methods Multiclass classification Multi-label classification One-class classification Prosecutor's...

examples of settings for MTL include multiclass classification and multi-label classification. Multi-task learning works because regularization induced...

can also be extended to Multi-label classification (where multiple classes can be predicted at once) and soft-label classification (where classes can be...

videos for tasks such as object detection, facial recognition, and multi-label classification. See (Calli et al, 2015) for a review of 33 datasets of 3D object...

Gunk (mereology) Multicategory Multiclass classification, Multicriteria classification, Multi-label classification Multigraph Multiple inheritance Polysemy...

transformation in multi-label classification. It combines the computational efficiency of the binary relevance method while still being able to take the label dependencies...

Anomaly detection Association rules Bias-variance dilemma Classification Multi-label classification Clustering Data Pre-processing Empirical risk minimization...

be called a taxonomy). Or it may refer to the label given to an object by the classifier. Classification is a part of many different kinds of activities...

South Wales, 2002. Graves, Alex, et al. "Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks." Proceedings...

individually labeled, the learner receives a set of labeled bags, each containing many instances. In the simple case of multiple-instance binary classification, a...

Geoff; Pfahringer, Bernhard (2012). "Scalable and efficient multi-label classification for evolving data streams". Machine Learning. 88 (1–2): 243–272...

called Extreme Classification (also known as Extreme Multi-label Classification). Extreme Classification focuses on Multi-Label Classification at the scale...

Categorical perception Categorization Discrimination Master status Multi-label classification Prejudice Self-categorization theory Social stigma Stereotype...

group-label to each new observation. Classification can be thought of as two separate problems – binary classification and multiclass classification. In...

Solving Assistants, Arlington, VA, November 2005. Collective Multi-Label Classification, Nadia Ghamrawi and Andrew McCallum. CIKM'05, Bremen, Germany...

include multi-task learning (also called multi-output learning or vector-valued learning), transfer learning, and co-kriging. Multi-label classification can...

weights, and thus two hyperplanes. This can then be generalized for multi-label classification. In certain circumstances, it can be shown that the number of...

Characterization (mathematics) Classification (general theory) Knolling Library classification Multi-label classification Pattern recognition Shared intentionality...

In the classification phase, k is a user-defined constant, and an unlabeled vector (a query or test point) is classified by assigning the label which is...

Muhammad Tanvir; Sulaiman, Muhammad; Shahid, Abdul (2021-11-09). "Multi-label classification of research articles using Word2Vec and identification of similarity...

(2021). "Enzyme promiscuity prediction using hierarchy-informed multi-label classification". Bioinformatics. 37 (14): 2017–2024. doi:10.1093/bioinformatics/btab054...

In astronomy, stellar classification is the classification of stars based on their spectral characteristics. Electromagnetic radiation from the star is...

Labeled data is a group of samples that have been tagged with one or more labels. Labeling typically takes a set of unlabeled data and augments each piece...

instead of simply a single best label. When the number of possible labels is fairly small (e.g., in the case of classification), N may be set so that the probability...

Organic RFID Circuit with an Integrated Sensor for Smart Labels" (PDF). 9th International Multi-Conference on Systems, Signals and Devices. Retrieved 26...

a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions...

An auxiliary label (also called cautionary and advisory label or prescription drug warning label) is a label added on to a dispensed medication package...

overwhelmed by uninformative examples. Recent developments are dedicated to multi-label active learning, hybrid active learning and active learning in a single-pass...