Suche mittels Attribut

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Suche mittels Attribut

Eine Liste aller Seiten, die das Attribut „Kurzfassung“ mit dem Wert „In today’s world, most datasets do not have only a small number of attributes. The high number of attributes, which are referred to as dimensions, hinder the search of objects that normally not occur. For instance, consider a money transaction that has been not legally carried out. Such objects are called outlier. A common method to detect outliers in high dimensional datasets are based on the search in subspaces of the dataset. These subspaces have the characteristics to reveal possible outliers. The most common evaluation of algorithms searching for subspaces is based on benchmark datasets. However, the benchmark datasets are often not suitable for the evaluation of these subspace search algorithms. In this context, we present a method that evaluates subspace search algorithms without relying on benchmark datasets by hiding outliers in the result set of a subspace search algorithm.“ haben. Weil nur wenige Ergebnisse gefunden wurden, werden auch ähnliche Werte aufgelistet.

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Liste der Ergebnisse

    • Evaluating Subspace Search Methods with Hidden Outlier  + (In today’s world, most datasets do not hav … In today’s world, most datasets do not have only a small number of attributes. The high</br>number of attributes, which are referred to as dimensions, hinder the search of objects</br>that normally not occur. For instance, consider a money transaction that has been not</br>legally carried out. Such objects are called outlier. A common method to detect outliers</br>in high dimensional datasets are based on the search in subspaces of the dataset. These</br>subspaces have the characteristics to reveal possible outliers. The most common evaluation of algorithms searching for subspaces is based on benchmark datasets. However, the</br>benchmark datasets are often not suitable for the evaluation of these subspace search algorithms. In this context, we present a method that evaluates subspace search algorithms</br>without relying on benchmark datasets by hiding outliers in the result set of a subspace</br>search algorithm.result set of a subspace search algorithm.)
    Abgerufen von „https://sdq.kastel.kit.edu/institutsseminar/Spezial:Suche_mittels_Attribut“