Interdependence between CHD risk factors examined using linear models with and without transformation of data
A. Bartkowiak, S. Łukasik, K. Chwistecki, M. Mrukowicz (1988)
Applicationes Mathematicae
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A. Bartkowiak, S. Łukasik, K. Chwistecki, M. Mrukowicz (1988)
Applicationes Mathematicae
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Ammar Shaker, Eyke Hüllermeier (2014)
International Journal of Applied Mathematics and Computer Science
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In this paper, we introduce a method for survival analysis on data streams. Survival analysis (also known as event history analysis) is an established statistical method for the study of temporal “events” or, more specifically, questions regarding the temporal distribution of the occurrence of events and their dependence on covariates of the data sources. To make this method applicable in the setting of data streams, we propose an adaptive variant of a model that is closely related to...
Liu Bin, Zhang Hui, Liu Sifeng, Dang Yaoguo (2006)
Computer Science and Information Systems
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Zhaowei, Shang, Lingfeng, Zhang, Shangjun, Ma, Bin, Fang, Taiping, Zhang (2010)
Mathematical Problems in Engineering
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Dubravka Bošković, Srđan Popov, Miro Govedarica (2009)
Review of the National Center for Digitization
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Semih Önüt, Fuat Güney, Tufan Demirel, Halil Ibrahim Erdem (1994)
The Yugoslav Journal of Operations Research
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Enrico Carlon (2008)
Banach Center Publications
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DNA microarrays have been widely used in molecular biology laboratories. The main current application of these devices is the determination of the gene expression level for thousands of genes simultaneously. Here we review a recently introduced physical model for hybridization (i.e. the binding of complementary DNA strands) in Affymetrix arrays and compare it to experimental results. The experimental data follow rather well the microscopic model and the approach offers several advantages...
Ljiljana Kašćelan, Dragana Bečejski-Vujaklija (2005)
Computer Science and Information Systems
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Y. W. Teh (2004)
Mathware and Soft Computing
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With the availability of very large data storage today, redundant data structures are no longer a big issue. However, an intelligent way of managing materialised projection and selection views that can lead to fast access of data is the central issue dealt with in this paper. A set of implementation steps for the data warehouse administrators or decision makers to improve the response time of queries is also defined. The study concludes that both attributes and tuples, are important...
Miroslav Kárný, Tomáš Jeníček, Werner Ottenheimer (1990)
Kybernetika
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David Pearson (2007)
International Journal of Applied Mathematics and Computer Science
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In this paper we introduce a method of classification based on data probes. Data points are considered as point masses in space and a probe is simply a particle that is launched into the space. As the probe passes by data clusters, its trajectory will be influenced by the point masses. We use this information to help us to find vertical trajectories. These are trajectories in the input space that are mapped onto the same value in the output space and correspond to the data classes. ...
Terje Loken, Jan Komorowski (2001)
International Journal of Applied Mathematics and Computer Science
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Traditional data mining methods based on rough set theory focus on extracting models which are good at classifying unseen obj-ects. If one wants to uncover new knowledge from the data, the model must have a high descriptive quality-it must describe the data set in a clear and concise manner, without sacrificing classification performance. Rough modeling, introduced by Kowalczyk (1998), is an approach which aims at providing models with good predictive emphand descriptive qualities, in...