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Active learning (machine learning)

Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source) to label new data points with the desired outputs. The human user must possess expertise in the problem domain, including the ability to consult authoritative sources when necessary. In statistics…

Products, Scenarios & Query strategies

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Explore the main themes, entities and connections around Active learning (machine learning). Start with the topic map, then use the sections below for research and deeper semantic analysis.

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Map overview Semantic statistics

Active learning (machine learning)

Nodes24
Edges23
Triples2
Avg. degree1.92
Density0.083333
Components1

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Important terminology Word statistics

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Important terminology

data learning active label points query algorithm machine teacher instances would human also labeled sampling algorithms learner examples current methods

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Amazon Mechanical Turk that include many humans in the active learning loopinstance ofwhen comparative updates would require a quantum or super computer.Large-scale active learning projects may benefit from crowdsourcing frameworks0.80text
logistic regression or SVM that yields class-membership probabilities for individual data instancesinstance ofIt is often initially trained on a fully labeled subset of the data using a machine-learning method0.80text

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