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Klyngeanalyse og dimensionsreduktion

61 metoder i denne familie.

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Aktive lærings-associationsreglerActive learning association rules combines the iterative query-and-label loop of active learning with association rule mining, allowing a human expert to guide the discovery procesAktiv læring autoencoder anomalidetektionActive Learning Autoencoder Anomaly Detection combines an autoencoder's unsupervised reconstruction-error scoring with an active learning query loop. The model flags high-error insActive Learning Isolation ForestActive Learning Isolation Forest combines the unsupervised anomaly-scoring power of Isolation Forest with an iterative query strategy that asks a human expert to label the most infAffinity Propagation ClusteringAffinity propagation, introduced by Brendan Frey and Delbert Dueck in 2007, is a clustering algorithm that identifies representative 'exemplars' among the data by exchanging messagApriori AlgoritmenThe Apriori algorithm, introduced by Agrawal and Srikant in 1994, is the foundational method for discovering frequent itemsets and association rules in transactional databases. It Association Rule Mining (Apriori)Association Rule Mining is an unsupervised data-mining technique that discovers co-occurrence patterns among items in transactional datasets. Formally introduced by Agrawal, Imieli

Læsesti

Dette emnes mest refererede grundlæggende metoder, i den rækkefølge de blev udviklet — et godt sted at begynde, hvis du er ny her.

  1. Hierarkisk gruppering1963af Ward, J. H.
  2. K-means Clustering1967 (formalized 1982)af MacQueen, J. B.; Lloyd, S. P.
  3. K-Means Clustering1967af MacQueen, J.
  4. DBSCAN1996af Ester, M., Kriegel, H.-P., Sander, J. & Xu, X.
  5. One-Class SVM1999–2001af Scholkopf, B., Platt, J. C., Smola, A. J., Williamson, R. C.
  6. Principal Component Analysis2002af Jolliffe, I.T. (textbook); Pearson & Hotelling (origins)
  7. Autoencoder Anomalidetektion2006–2014af Hinton, G. E. & Salakhutdinov, R. R. (autoencoders); applied to anomaly detection through multiple authors in the 2010s
  8. Isolation Forest2008af Liu, F.T., Ting, K.M. & Zhou, Z.-H.
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Aktive lærings-associationsreglerAktiv læring autoencoder anomalidetektionActive Learning Isolation ForestAffinity Propagation ClusteringApriori AlgoritmenAssociation Rule Mining (Apriori)AssocieringsreglerAutoencoder AnomalidetektionBIRCHDBSCANECLAT Frequent-Itemset MiningEnsemble Apriori AlgoritmenEnsemble Association RulesEnsemble Autoencoder Anomaly DetectionEnsemble HDBSCANEnsemble Isolation ForestEnsemble K-meansFuzzy C-Means Clustering (FCM)Gaussisk BlandingsmodelHDBSCANHierarkisk grupperingIsolation ForestK-means ClusteringK-Means ClusteringKernel PCALocal Outlier Factor (LOF)Lokalt Lineær Indlejring (LLE)Mean ShiftOne-Class SVMOnline Association RulesOnline Autoencoder AnomalidetektionOnline DBSCANOnline HDBSCANOnline Isolation ForestOnline K-meansOPTICSPrincipal Component AnalysisPrincipal Components Regression (PCR)Tilfældig projektionReguleret Gaussisk Blanding (GMM)Regulariseret K-Means-klyngedannelseRobust Autoencoder Anomaly DetectionRobust HDBSCANRobust Isolation ForestRobust k-meansSelf-Organizing Map (Kohonen Map)Selv-overvåget autoencoder anomalidetektionSelv-overvåget DBSCANSelv-overvåget Gaussisk BlandingsmodelSelf-supervised Isolation ForestSelv-superviseret K-meansSemi-overvåget Apriori-algoritmeSemiovervågede associationsreglerSemi-overvåget Autoencoder AnomalidetektionSemi-superviseret DBSCANSemi-supervised HDBSCANSemi-supervised Isolation ForestSemi-overvåget K-meansSpektral klyngedannelset-SNEUMAP