Unsupervised learning: Difference between revisions

Revision as of 05:06, 26 April 2024

Revision as of 05:10, 26 April 2024

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{{Short description|A paradigm in machine learning}}

'''Unsupervised learning''' is a method in [[machine learning]] where, in contrast to [[supervised learning]], algorithms learn patterns exclusively from unlabeled data.<ref name="WeiWu">{{Cite web |last=Wu |first=Wei |title=Unsupervised Learning |url=https://na.uni-tuebingen.de/ex/ml_seminar_ss2022/Unsupervised_Learning%20Final.pdf |url-status=live |access-date=26 April 2024}}</ref> TheWithin hopesuch isan that through mimicryapproach, whicha ismachine anlearning importantmodel modetries ofto learningfind inany peoplesimilarities, thedifferences, machinepatterns, isand forcedstructure toin builddata aby conciseitself. representationNo ofprior itshuman worldintervention andis thenneeded.<ref generatename="WeiWu" imaginative content from it./>

Other methods in the supervision spectrum are [[Reinforcement Learning]] where the machine is given only a numerical performance score as guidance, and [[Weak_supervision | Weak or Semi supervision]] where a small portion of the data is tagged, and [[Self-supervised_learning | Self Supervision]].