6 items found

Types: DataMiner Process Tags: Data Clustering

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    DataMiner Process

    Private Lof in AGINFRAplus

    Local Outlier Factor (LOF). A clustering algorithm for real valued vectors that relies on Local Outlier Factor algorithm, i.e. an algorithm for finding anomalous data points by...
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    DataMiner Process

    Private Dbscan in AGINFRAplusDev

    A clustering algorithm for real valued vectors that relies on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. A maximum of 4000 points is...
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    DataMiner Process

    Private Xmeans in AGINFRAplus

    A clustering algorithm for occurrence points that relies on the X-Means algorithm, i.e. an extended version of the K-Means algorithm improved by an Improve-Structure part. A...
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    DataMiner Process

    Private Kmeans in AGINFRAplus

    A clustering algorithm for real valued vectors that relies on the k-means algorithm, i.e. a method aiming to partition n observations into k clusters in which each observation...
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    DataMiner Process

    Private Dbscan in AGINFRAplus

    A clustering algorithm for real valued vectors that relies on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. A maximum of 4000 points is...
  • Access required...

    ×

    DataMiner Process

    Private Dbscan in AGINFRAplusDev

    A clustering algorithm for real valued vectors that relies on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. A maximum of 4000 points is...