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...

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...

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

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

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

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

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...

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

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

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

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

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

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

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

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

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

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...

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

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...

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

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

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...

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

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...

order to boost performance on a related task. For example, for image classification, knowledge gained while learning to recognize cars could be applied...

Ecolabels (also "eco-Labels") and Green Stickers are labeling systems for food and consumer products. The use of ecolabels is voluntary, whereas green...

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