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Resultats globals: 6 registres trobats en 0.03 segons.
Articles, 6 registres trobats
Articles 6 registres trobats  
1.
43 p, 23.3 MB Identifying and Classifying Aberrant Response Patterns Through Functional Data Analysis / Doval Dieguez, Eduardo (Universitat Autònoma de Barcelona. Departament de Psicobiologia i de Metodologia de Ciències de la Salut) ; Delicado, Pedro (Universitat Autònoma de Barcelona. Departament de Psicobiologia i de Metodologia de Ciències de la Salut)
We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. [...]
Elsevier 2020 - 10.3102/1076998620911941
Journal of Educational and Behavioral Statistics, Vol. 45 Núm. 6 (2020) , p. 719-749  
Registre complet -
2.
10 p, 659.4 KB A Flexible Outlier Detector Based on a Topology Given by Graph Communities / Ramos Terrades, Oriol (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació) ; Berenguel Centeno, Albert (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació) ; Gil, Debora (Centre de Visió per Computador (Bellaterra, Catalunya))
Outlier detection is essential for optimal performance of machine learning methods and statistical predictive models. Their detection is especially determinant in small sample size unbalanced problems, since in such settings outliers become highly influential and significantly bias models. [...]
2022 - 10.1016/j.bdr.2022.100332
Big Data Research, Vol. 29 (August 2022) , art. 100332  
Registre complet - Creative Commons
3.
20 p, 395.8 KB Joint outlier detection and variable selection using discrete optimization / Jammal, Mahdi ; Canu, Stephane ; Abdallah, Maher
In regression, the quality of estimators is known to be very sensitive to the presence of spurious variables and outliers. Unfortunately, this is a frequent situation when dealing with real data. To handle outlier proneness and achieve variable selection, we propose a robust method performing the outright rejection of discordant observations together with the selection of relevant variables. [...]
2021 - 10.2436/20.8080.02.109
SORT : statistics and operations research transactions, Vol. 45 Núm. 1 (January-June 2021) , p. 47-66 (Articles)  
Registre complet - Creative Commons
4.
24 p, 1.9 MB Automatic Date Fruit Recognition Using Outlier Detection Techniques and Gaussian Mixture Models / Aiadi, Oussama (University of Kasdi Marbah (Ouargla, Algèria.) LAGE Laboratory) ; Kherfi, Mohammed Lamine (Université du Québec à Trois-Rivières. LAMIA Laboratory) ; Khaldi, Belal (University of Kasdi Marbah (Ouargla, Algèria.) LAGE Laboratory)
In this paper, we propose a method for automatically recognizing different date varieties. The presence of outlier samples could significantly degrade the recognition outcomes. Therefore, we separately prune samples of each variety from outliers using the Pruning Local Distance-based Outlier Factor (PLDOF) method. [...]
2019 - 10.5565/rev/elcvia.1041
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 1 (2019) , p. 52-75 (Regular Issue)  
Registre complet - Creative Commons
5.
28 p, 700.0 KB Using robust FPCA to identify outliers in functional time series, with applications to the electricity market / Vilar, Juan M. (Universidade da Coruña. Departamento de Matemáticas) ; Raña, Paula (Universidade da Coruña. Departamento de Matemáticas) ; Aneiros, Germán (Universidade da Coruña. Departamento de Matemáticas)
This study proposes two methods for detecting outliers in functional time series. Both methods take dependence in the data into account and are based on robust functional principal component analysis. [...]
2016
SORT : statistics and operations research transactions, Vol. 40 Núm. 2 (July-December 2016) , p. 321-348 (Articles)  
Registre complet - Creative Commons
6.
15 p, 1.3 MB Combining Model-based and Discriminative Approaches in a Modular Two-stage Classification System : application to Isolated Handwritten Digit Recognition / Milgram, Jonathan (Université du Québec. École de Technologie Supérieure) ; Sabourin, Robert (Université du Québec. École de Technologie Supérieure) ; Cheriet, Mohamed (Université du Québec. École de Technologie Supérieure)
The motivation of this work is based on two key observations. First, the classification algorithms can be separated into two main categories: discriminative and model-based approaches. Second, two types of patterns can generate problems: ambiguous patterns and outliers. [...]
2005 - 10.5565/rev/elcvia.92
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 5 n. 2 (2005) p. 1-15  
Registre complet - Creative Commons

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