102 lines
4.2 KiB
Markdown
102 lines
4.2 KiB
Markdown
---
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title: "ELKI"
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chunk: 2/2
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source: "https://en.wikipedia.org/wiki/ELKI"
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category: "reference"
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tags: "science, encyclopedia"
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date_saved: "2026-05-05T10:11:18.253498+00:00"
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instance: "kb-cron"
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---
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Cluster analysis:
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K-means clustering (including fast algorithms such as Elkan, Hamerly, Annulus, and Exponion k-Means, and robust variants such as k-means--)
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K-medians clustering
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K-medoids clustering (PAM) (including FastPAM and approximations such as CLARA, CLARANS)
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Expectation-maximization algorithm for Gaussian mixture modeling
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Hierarchical clustering (including the fast SLINK, CLINK, NNChain and Anderberg algorithms)
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Single-linkage clustering
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Leader clustering
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DBSCAN (Density-Based Spatial Clustering of Applications with Noise, with full index acceleration for arbitrary distance functions)
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OPTICS (Ordering Points To Identify the Clustering Structure), including the extensions OPTICS-OF, DeLi-Clu, HiSC, HiCO and DiSH
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HDBSCAN
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Mean-shift clustering
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BIRCH clustering
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SUBCLU (Density-Connected Subspace Clustering for High-Dimensional Data)
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CLIQUE clustering
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ORCLUS and PROCLUS clustering
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COPAC, ERiC and 4C clustering
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CASH clustering
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DOC and FastDOC subspace clustering
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P3C clustering
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Canopy clustering algorithm
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Anomaly detection:
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k-Nearest-Neighbor outlier detection
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LOF (Local outlier factor)
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LoOP (Local Outlier Probabilities)
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OPTICS-OF
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DB-Outlier (Distance-Based Outliers)
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LOCI (Local Correlation Integral)
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LDOF (Local Distance-Based Outlier Factor)
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EM-Outlier
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SOD (Subspace Outlier Degree)
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COP (Correlation Outlier Probabilities)
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Frequent Itemset Mining and association rule learning
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Apriori algorithm
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Eclat
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FP-growth
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Dimensionality reduction
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Principal component analysis
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Multidimensional scaling
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T-distributed stochastic neighbor embedding (t-SNE)
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Spatial index structures and other search indexes:
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R-tree
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R*-tree
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M-tree
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k-d tree
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X-tree
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Cover tree
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iDistance
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NN descent
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Locality sensitive hashing (LSH)
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Evaluation:
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Precision and recall, F1 score, Average Precision
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Receiver operating characteristic (ROC curve)
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Discounted cumulative gain (including NDCG)
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Silhouette index
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Davies–Bouldin index
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Dunn index
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Density-based cluster validation (DBCV)
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Visualization
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Scatter plots
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Histograms
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Parallel coordinates (also in 3D, using OpenGL)
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Other:
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Statistical distributions and many parameter estimators, including robust MAD based and L-moment based estimators
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Dynamic time warping
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Change point detection in time series
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Intrinsic dimensionality estimators
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== Version history ==
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Version 0.1 (July 2008) contained several Algorithms from cluster analysis and anomaly detection, as well as some index structures such as the R*-tree. The focus of the first release was on subspace clustering and correlation clustering algorithms.
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Version 0.2 (July 2009) added functionality for time series analysis, in particular distance functions for time series.
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Version 0.3 (March 2010) extended the choice of anomaly detection algorithms and visualization modules.
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Version 0.4 (September 2011) added algorithms for geo data mining and support for multi-relational database and index structures.
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Version 0.5 (April 2012) focuses on the evaluation of cluster analysis results, adding new visualizations and some new algorithms.
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Version 0.6 (June 2013) introduces a new 3D adaption of parallel coordinates for data visualization, apart from the usual additions of algorithms and index structures.
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Version 0.7 (August 2015) adds support for uncertain data types, and algorithms for the analysis of uncertain data.
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Version 0.7.5 (February 2019) adds additional clustering algorithms, anomaly detection algorithms, evaluation measures, and indexing structures.
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Version 0.8 (October 2022) adds automatic index creation, garbage collection, and incremental priority search, as well as many more algorithms such as BIRCH.
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== Similar applications ==
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scikit-learn: machine learning library in Python
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Weka: A similar project by the University of Waikato, with a focus on classification algorithms
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RapidMiner: An application available commercially (a restricted version is available as open source)
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KNIME: An open source platform which integrates various components for machine learning and data mining
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== See also ==
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Comparison of statistical packages
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== References ==
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== External links ==
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Official website of ELKI with download and documentation. |