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  2. DBSCAN - Wikipedia

    en.wikipedia.org/wiki/DBSCAN

    Every data mining task has the problem of parameters. Every parameter influences the algorithm in specific ways. For DBSCAN, the parameters ε and minPts are needed. The parameters must be specified by the user. Ideally, the value of ε is given by the problem to solve (e.g. a physical distance), and minPts is then the desired minimum cluster ...

  3. OPTICS algorithm - Wikipedia

    en.wikipedia.org/wiki/OPTICS_algorithm

    Like DBSCAN, OPTICS requires two parameters: ε, which describes the maximum distance (radius) to consider, and MinPts, describing the number of points required to form a cluster. A point p is a core point if at least MinPts points are found within its ε -neighborhood N ε ( p ) {\displaystyle N_{\varepsilon }(p)} (including point p itself).

  4. SUBCLU - Wikipedia

    en.wikipedia.org/wiki/SUBCLU

    SUBCLU is an algorithm for clustering high-dimensional data by Karin Kailing, Hans-Peter Kriegel and Peer Kröger. [1] It is a subspace clustering algorithm that builds on the density-based clustering algorithm DBSCAN.

  5. ELKI - Wikipedia

    en.wikipedia.org/wiki/ELKI

    The Java just-in-time compiler optimizes all combinations to a similar extent, making benchmarking results more comparable if they share large parts of the code. When developing new algorithms or index structures, the existing components can be easily reused, and the type safety of Java detects many programming errors at compile time.

  6. Java Community Process - Wikipedia

    en.wikipedia.org/wiki/Java_Community_Process

    The Java Community Process (JCP), established in 1998, is a formal mechanism that enables interested parties to develop standard technical specifications for Java technology. Becoming a member of the JCP requires solid knowledge of the Java programming language, its specifications, and best practices in software development.

  7. Talk:DBSCAN - Wikipedia

    en.wikipedia.org/wiki/Talk:DBSCAN

    GPL-V3 Java implementations of more than 80 data mining algorithms. It offers an efficient Java implementation of the DBScan algorithm using a KD-Tree that is easy to integrate in other Java software. A GUI and command line interface is provided. This is advertisement text.

  8. Java (programming language) - Wikipedia

    en.wikipedia.org/wiki/Java_(programming_language)

    Java is a high-level, class-based, object-oriented programming language that is designed to have as few implementation dependencies as possible. It is a general-purpose programming language intended to let programmers write once, run anywhere (), [16] meaning that compiled Java code can run on all platforms that support Java without the need to recompile. [17]

  9. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...