The GeneratorXMLSpec can be invoked from the command line using Invocationīeginning with ELKI 0.7.1, you can choose the generator in the MiniGUI. This can be disabled by setting the test-model="0" attribute of the dataset element. This is enabled by default (or explicitly by setting the test-model="1" attribute of the dataset element). When using this option, you should be aware of the risk of overfitting (but you should be aware of this when using artificial data anyway!). In particular when generating outlier detection data sets, you can easily avoid producing background noise within a dense cluster (which by definition would no longer be an outlier). This leads to some drawbacks - some models will not be satisfiable, and the generator will stop after a number of retries - but it also has many benefits when using the labels for validating clustering results. Only data points that classify as the same cluster they were generated for will be kept. Gold standard generationįor a gold standard, the model specification serves a dual purpose: it is not only used to generate the points, but at the same time also to classify them. There currently is no support for clipping inbetween over transformations. The generation flow is to produce random values using the given distributions, then apply the rotations and translations in order (optimized using homogeneous coordinates, so you can put in as many operations as you want with minimal cost), then finally clipping is applied. Obviously, all clusters in the data set must have the same number of dimensions, and for each dimension you need to specify the distribution to use. Basic cluster definitionĪ typical cluster definition (cluster model): Allows arbitrary rotations, translations and scaling of generated clusters to generate correlated data setsĪ full XML schema definition can be found in the ELKI jar file. Can generate non-overlapping clusters of specified size.
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