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Clustering techniques applied to outlier detection of financial market series using a moving window filtering algorithm
Puigvert Gutiérrez, Josep Maria; Fortiana Gregori, Josep - 2008
In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data … outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset … of a cluster that represents a different segment of the market. We set up a framework of possible algorithm parameter …
Persistent link: https://www.econbiz.de/10011604994
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Rating Companies with Support Vector Machines
Schäfer, Dirk; Moro, R. A.; Härdle, Wolfgang Karl - 2004
utilise their classification power. …
Persistent link: https://www.econbiz.de/10010276551
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Stock picking via nonsymmetrically pruned binary decision trees
Andriyashin, Anton - 2008
researchers. In this study stock picking is implemented via binary classification trees. Optimal tree size is believed to be the …
Persistent link: https://www.econbiz.de/10010263732
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Machine Learning in der amtlichen Statistik – Ergebnisse und Bewertung eines internationalen Projekts
Dumpert, Florian - In: WISTA – Wirtschaft und Statistik 73 (2021) 4, pp. 53-63
Die High-Level-Group for the Modernization of Official Statistics der Wirtschaftskommission der Vereinten Nationen für Europa hatte für die Jahre 2019 und 2020 ein Machine-Learning-Projekt initiiert. Das Projekt ermöglichte die Durchführung von Pilotstudien, um den Mehrwert maschinellen...
Persistent link: https://www.econbiz.de/10012604546
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Fast nonparametric classification based on data depth
Lange, Tatjana; Mosler, Karl; Mozharovskyi, Pavlo - 2012
classes. The procedure is completely nonparametric; it uses q-dimensional depth plots and a very efficient algorithm for … discrimination analysis in the depth space [0, 1]q . Specifically, the depth is the zonoid depth, and the algorithm is the procedure … cases the new procedure has comparable error rates, but is much faster than other classification approaches, including the …
Persistent link: https://www.econbiz.de/10010311009
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Machine Learning im Logistikmanagement: Entwicklung eines Gestaltungsansatzes zum Einsatz von ML-Anwendungen in logistischen Entscheidungsprozessen
Weinke, Manuel - 2023
Als ein Teilbereich der Künstlichen Intelligenz stellt Machine Learning (ML) eine Schüsseltechnologie des 21. Jahrhunderts dar. Unter Nutzung der mathematisch-statistischen Verfahren sind technische Systeme realisierbar, die anhand von Daten eigenständig empirische Zusammenhänge erkennen und...
Persistent link: https://www.econbiz.de/10014433975
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Implikationen von Machine Learning auf das Datenmanagement in Unternehmen
Kessler, René; Gómez, Jorge Marx - In: HMD Praxis der Wirtschaftsinformatik 57 (2020) 1, pp. 89-105
Machine Learning ist ein Forschungsfeld mit großen Potenzialen und weitreichenden Anwendungspotenzialen. Big Data kann dabei als Enabler angesehen werden, da große und qualitativ hochwertige Daten stets die Grundlage für erfolgreiche Machine Learning-Algorithmen und -Modelle darstellen....
Persistent link: https://www.econbiz.de/10014504476
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Reducing the 0-1 knapsack problem with a single continuous variable to the standard 0-1 knapsack problem
Büther, Marcel; Briskorn, Dirk - 2007
The 0-1 knapsack problem with a single continuous variable (KPC) is a natural extension of the binary knapsack problem (KP), where the capacity is not any longer fixed but can be extended which is expressed by a continuous variable. This variable might be unbounded or restricted by a lower or...
Persistent link: https://www.econbiz.de/10011558835
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Pricing the multiple-choice nested knapsack problem
Drexl, Andreas; Jørnsten, Kurt - 2007
The multiple-choice nested knapsack problem (MCKP) is a generalization of the ordinary knapsack problem, where the set of items is partitioned into classes. The binary choice of selecting an item is replaced by taking exactly one item out of each class of items. Due to the fact that the MCKP is...
Persistent link: https://www.econbiz.de/10011558832
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Cost Sharing under Uncertainty: An Algorithmic Approach to Cooperative Interval-Valued Games
Kimms, Alf; Drechsel, Julia - In: BuR - Business Research 2 (2009) 2, pp. 206-213
will present a general mathematical programming algorithm which can be applied to find an element in the interval core. As …
Persistent link: https://www.econbiz.de/10010421344