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Pengelompokan dan penurunan dimensi

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Aturan Asosiasi Pembelajaran AktifActive 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 procesPengesanan Anomali Autoenkoder Pembelajaran AktifActive Learning Autoencoder Anomaly Detection combines an autoencoder's unsupervised reconstruction-error scoring with an active learning query loop. The model flags high-error insIsolation Forest Pembelajaran AktifActive 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 infPengepulan Pecutan KesetiaanAffinity propagation, introduced by Brendan Frey and Delbert Dueck in 2007, is a clustering algorithm that identifies representative 'exemplars' among the data by exchanging messagAlgoritma AprioriThe Apriori algorithm, introduced by Agrawal and Srikant in 1994, is the foundational method for discovering frequent itemsets and association rules in transactional databases. It Galian Peraturan Persatuan (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

Laluan bacaan

Kaedah asas yang paling banyak dirujuk bagi topik ini, mengikut susunan ia dibangunkan — tempat untuk bermula jika anda baharu di sini.

  1. Pencapanian Hierarkis1963oleh Ward, J. H.
  2. PengeLCManan K-means1967 (formalized 1982)oleh MacQueen, J. B.; Lloyd, S. P.
  3. Pengelompokan K-Means1967oleh MacQueen, J.
  4. DBSCAN1996oleh Ester, M., Kriegel, H.-P., Sander, J. & Xu, X.
  5. SVM Kelas Tunggal1999–2001oleh Scholkopf, B., Platt, J. C., Smola, A. J., Williamson, R. C.
  6. Analisis Komponen Utama2002oleh Jolliffe, I.T. (textbook); Pearson & Hotelling (origins)
  7. Pengesanan Anomali Autoenkoder2006–2014oleh Hinton, G. E. & Salakhutdinov, R. R. (autoencoders); applied to anomaly detection through multiple authors in the 2010s
  8. Isolation Forest2008oleh Liu, F.T., Ting, K.M. & Zhou, Z.-H.
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Aturan Asosiasi Pembelajaran AktifPengesanan Anomali Autoenkoder Pembelajaran AktifIsolation Forest Pembelajaran AktifPengepulan Pecutan KesetiaanAlgoritma AprioriGalian Peraturan Persatuan (Apriori)Peraturan PersatuanPengesanan Anomali AutoenkoderBIRCHDBSCANGalian Set-Item Frekuen ECLATAlgoritma Ensemble AprioriAturan Persatuan EnsemblePengesanan Anomali Ensemble AutoencoderEnsemble HDBSCANEnsemble Isolation ForestEnsemble K-meansPengelompokan Kabur C-Means (FCM)Model Campuran GaussianHDBSCANPencapanian HierarkisIsolation ForestPengeLCManan K-meansPengelompokan K-MeansPCA KernelFaktor Penyimpang Lokal (LOF)Locally Linear Embedding (LLE)Mean ShiftSVM Kelas TunggalPeraturan Persatuan Dalam TalianPengesanan Anomali Autoencoder Dalam TalianDBSCAN Dalam TalianOnline HDBSCANOnline Isolation ForestK-means Atar (Online K-means)OPTICSAnalisis Komponen UtamaRegresi Komponen Utama (PCR)Projeksi RawakModel Campuran Gaussian TerregulasiKlusterisasi K-Means TerregulasiPengesanan Anomali Autoenkoder TeguhRobust HDBSCANHutan Isolasi RobustRobust k-meansPeta Pengatur Diri (Peta Kohonen)Pengesanan Anomali Autoenkoder Penyeliaan KendiriDBSCAN kendiri-seliaModel Campuran Gaussian Kendiri-terlarasIsolation Forest Penyeliaan KendiriK-means Kendiri-seliaAlgoritma Apriori Separuh-TerbimbingPeraturan Persatuan Separuh TerawasiPengesanan Anomali Autoencoder Separuh SempurnaDBSCAN Separuh-BimbinganHDBSCAN Separuh-SeliaHutan Pengasingan Separa Sedia TerkawalK-means separa-pengawasanPengelompokan Spektralt-SNEUMAP