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SUBCLU is an algorithm for clustering high-dimensional data by Karin Kailing, Hans-Peter Kriegel and Peer Kröger. It is a subspace clustering algorithm
SUBCLU
Density-based data clustering algorithm
is also used as part of subspace clustering algorithms like PreDeCon and SUBCLU. HDBSCAN* is a hierarchical version of DBSCAN which is also faster than
DBSCAN
Data mining framework
DeLi-Clu, HiSC, HiCO and DiSH HDBSCAN Mean-shift clustering BIRCH clustering SUBCLU (Density-Connected Subspace Clustering for High-Dimensional Data) CLIQUE
ELKI
Grouping a set of objects by similarity
their attributes. Examples for such clustering algorithms are CLIQUE and SUBCLU. Ideas from density-based clustering methods (in particular the DBSCAN/OPTICS
Cluster_analysis
Overview of and topical guide to machine learning
induction Rules extraction system family SAS (software) SNNS SPSS Modeler SUBCLU Sample complexity Sample exclusion dimension Santa Fe Trail problem Savi
Outline_of_machine_learning
Single-linkage clustering: a simple agglomerative clustering algorithm SUBCLU: a subspace clustering algorithm WACA clustering algorithm: a local clustering
List_of_algorithms
German computer scientist
X-tree and IQ-Tree, the cluster analysis algorithms DBSCAN, OPTICS and SUBCLU and the anomaly detection method Local Outlier Factor (LOF). His research
Hans-Peter_Kriegel
Method of data analysis
an approach taken by most of the traditional algorithms such as CLIQUE, SUBCLU. It is also possible to define a subspace using different degrees of relevance
Clustering high-dimensional data
Clustering_high-dimensional_data
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