Results 41 to 50 of about 23,619,888 (317)
An integrated approach for identifying wrongly labelled samples when performing classification in microarray data. [PDF]
PLoS ONE, 2012 Using hybrid approach for gene selection and classification is common as results obtained are generally better than performing the two tasks independently.
Yuk Yee Leung +2 more
doaj +1 more source
Outlier detection from ETL Execution trace
, 2011 Extract, Transform, Load (ETL) is an integral part of Data Warehousing (DW) implementation. The commercial tools that are used for this purpose captures lot of execution trace in form of various log files with plethora of information.
Chakrabarti, Amlan +2 more
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Liinc em Revista, 2013 Resumo Este artigo objetiva ilustrar a análise de outlier(s) aplicada aos cálculos bibliométricos. O Outlier é uma observação, elevada ou reduzida, em relação ao conjunto de dados. São três as causas possíveis para ocorrência de outlier: registro errado,
Luís Fernando Maia Lima +2 more
doaj +1 more source
Robust PCA as Bilinear Decomposition with Outlier-Sparsity Regularization [PDF]
, 2011 Principal component analysis (PCA) is widely used for dimensionality reduction, with well-documented merits in various applications involving high-dimensional data, including computer vision, preference measurement, and bioinformatics.
Giannakis, Georgios B., Mateos, Gonzalo
core +1 more source
Alphanumeric Journal, 2015 Yasam cozumlemesi, tanimlanan herhangi bir olayin ortaya cikmasina kadar gecen surenin incelenmesinde kullanilan istatistiksel yontemler butunudur. Yasam cozumlemesinde aykiri degerler klasik regresyonda kullanilan yontemlerden farkli yontemler kullanilarak hesaplanmaktadir. Yasam cozumlemesinde aykiri deger belirleme yontemleri artiklara ve artiklarin
KARASOY, Durdu, TUNCER, Nuray
openaire +2 more sources
Outliers in data envelopment analysis [PDF]
Journal of Centrum Cathedra, 2016 Purpose The purpose of this paper is to improve the estimation of the production frontier in cases where outliers exist. We focus on the case when outliers appear above the true frontier due to measurement error. Design/methodology/approach The authors use stochastic data envelopment analysis (SDEA) to allow observed points above the frontier.
Taylor Boyd, Grace Docken, John Ruggiero
openaire +1 more source
Outlier analysis of nonlinear solitary waves for health monitoring applications
Structural Health Monitoring, 2019 The structural health monitoring/nondestructive evaluation method based on the generation and detection of highly nonlinear solitary waves is emerging as a cost-effective technique to monitor or inspect a variety of structures and materials.
Bowen Zheng, P. Rizzo, A. Nasrollahi
semanticscholar +1 more source
Randomized Robust Subspace Recovery for High Dimensional Data Matrices
, 2016 This paper explores and analyzes two randomized designs for robust Principal Component Analysis (PCA) employing low-dimensional data sketching. In one design, a data sketch is constructed using random column sampling followed by low dimensional embedding,
Atia, George, Rahmani, Mostafa
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Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots
Cancer Informatics, 2006 We developed a quality assurance (QA) tool, namely microarray outlier filter (MOF), and have applied it to our microarray datasets for the identification of problematic arrays.
Song Yang +8 more
doaj +2 more sources
Genetic Variation and Breeding Signature in Mass Selection Lines of the Pacific Oyster (Crassostrea gigas) Assessed by SNP Markers. [PDF]
PLoS ONE, 2016 In breeding industries, a challenging problem is how to keep genetic diversity over generations. To investigate genetic variation and identify breeding signatures in mass selected lines of Pacific oyster (Crassostrea gigas), three sixth-generation ...
Xiaoxiao Zhong +4 more
doaj +1 more source