Výsledky vyhledávání

Elektronická kniha

Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings

Autor: Michael R. Berthold, Ad Feelders, Georg Krempl

This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected

Zobrazit plný text záznamu

Generating Realistic Natural Language Counterfactuals

Autor: Marcel Robeer, Floris Bex, Ad Feelders

Publikováno v: Findings of the Association for Computational Linguistics: EMNLP 2021.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cb6cfeaa33a10dccbbc9b9f3865ced3e
https://doi.org/10.18653/v1/2021.findings-emnlp.306

Zobrazit plný text záznamu

A validated method for estimating regional electricity demand from national time-series

Autor: Machteld van den Broek, Laurens Stoop, Ad Feelders

The share of renewable energy in the electrical grid will likely increase as mitigation measures for future climate change are put into effect. Renewable energy production, such as wind and solar, is largely dependent on the weather and is thus subje

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::83362cd4597547025b79777fc5a42381
https://doi.org/10.5194/egusphere-egu2020-15541

Zobrazit plný text záznamu

Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27-29, 2020, Proceedings

Autor: Ad Feelders, Michael R. Berthold, Georg Krempl

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030445836

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5cc138bf51f77e30d3f1479d09412351

Zobrazit plný text záznamu

Data-driven fraud detection in international shipping

Autor: Ron Triepels, Hennie Daniels, Ad Feelders

Publikováno v: Expert Systems with Applications, 99, 193. Elsevier Limited
Expert Systems with Applications, 99, 193-202. Elsevier Ltd.
Expert Systems with Applications, 99, 193-202. Elsevier Limited
Expert Systems with Applications, 99, 193-202. Elsevier Science

Document fraud constitutes a growing problem in international shipping. Shipping documentation may be deliberately manipulated to avoid shipping restrictions or customs duties. Well-known examples of such fraud are miscoding and smuggling. These are

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62261b618c4b0b38143f9f1802ea09ae
https://dspace.library.uu.nl/handle/1874/369305

Zobrazit plný text záznamu

Exceptional Model Mining

Autor: Ad Feelders, Wouter Duivesteijn, Arno Knobbe

Publikováno v: Data Mining and Knowledge Discovery. 30:47-98

Finding subsets of a dataset that somehow deviate from the norm, i.e. where something interesting is going on, is a classical Data Mining task. In traditional local pattern mining methods, such deviations are measured in terms of a relatively high oc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bc9e4bd6974a860c2b6c43801d5a7d3c
https://doi.org/10.1007/s10618-015-0403-4

Zobrazit plný text záznamu

Exploiting monotonicity constraints to reduce label noise: An experimental evaluation

Autor: Tijmen Kolkman, Ad Feelders

Publikováno v: IJCNN

In some ordinal classification problems we know beforehand that the class label should be increasing (or decreasing) in the attributes. Such relations between class label and attributes are called monotone. We attempt to exploit such monotonicity con

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::212b188d19439234102b559d76596d0e
https://doi.org/10.1109/ijcnn.2016.7727465

Zobrazit plný text záznamu

Exceptional Model Mining with Tree-Constrained Gradient Ascent

Autor: Thomas E. Krak, Ad Feelders

Publikováno v: SDM

Exceptional Model Mining (EMM) generalizes the wellknown data mining task of Subgroup Discovery (SD). Given a model class of interest, the goal of EMM is to find subgroups of the data for which a model fitted to the subgroup deviates substantially fr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bba83eb6a2152f82b2a80b3a241f19ad
https://doi.org/10.1137/1.9781611974010.55

Zobrazit plný text záznamu

A Quantitative Comparison of Semantic Web Page Segmentation Approaches

Autor: Ad Feelders, Jurriaan Hage, Robert Kreuzer

Publikováno v: Engineering the Web in the Big Data Era ISBN: 9783319198897
ICWE

We compare three known semantic web page segmentation algorithms, each serving as an example of a particular approach to the problem, and one self-developed algorithm, WebTerrain, that combines two of the approaches. We compare the performance of the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00c9f533f3c3adfdf785b6c6d3e3f781
https://dspace.library.uu.nl/handle/1874/325970

Zobrazit plný text záznamu

Confidence intervals for probabilistic network classifiers

Autor: Bart Baesens, Michael Egmont-Petersen, Ad Feelders

Publikováno v: Computational Statistics & Data Analysis, 49, 4, pp. 998-1019
Computational Statistics & Data Analysis, 49, 998-1019

Probabilistic networks (Bayesian networks) are suited as statistical pattern classifiers when the feature variables are discrete. It is argued that their white-box character makes them transparent, a requirement in various applications such as, e.g.,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1d3547829eaf57218ab4cf2a9e5d4cf
https://doi.org/10.1016/j.csda.2004.06.018

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání