Results 141 to 150 of about 3,980 (174)

Clinical risk prediction with multilinear sparse logistic regression

Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 2014
Logistic regression is one core predictive modeling technique that has been used extensively in health and biomedical problems. Recently a lot of research has been focusing on enforcing sparsity on the learned model to enhance its effectiveness and interpretability, which results in sparse logistic regression model.
Fei Wang 0001, Ping Zhang 0016, Buyue Qian, Xiang Wang 0001, Ian Davidson   +4 more
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Prediction of Calorific Value of Coal by Multilinear Regression and Analysis of Variance

Journal of Energy Resources Technology, 2021
Abstract The higher heating value (HHV) of 84 coal samples including hard coals, lignites, and anthracites from Russia, Colombia, South Africa, Turkey, and Ukrania was predicted by multilinear regression (MLR) method based on proximate and ultimate analysis data. The prediction accuracy of the correlation equations was tested by Analysis
M. Sözer, H. Haykiri-Acma, S. Yaman
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Influence of nonlinearities on estimates of respiratory mechanics using multilinear regression analysis

Journal of Applied Physiology, 1994
To investigate the influence of nonlinearities on estimates of respiratory mechanics, differing patterns of mechanical ventilation patterns were analyzed from 8 puppies and 14 children. Respiratory mechanics were calculated using multiple linear regression to fit a linear single-compartment model, a volume-dependent single-compartment model (VDSCM ...
Kano, S. H., Lanteri, C. J., Duncan, A. W., Sly, P. D.   +3 more
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Regression: Linear, Curvilinear and Multilinear

2003
Previously, we mainly dealt with univariate statistics, for observations that constitute a single measurement. They were presented in frequency-distribution graphs. The next step is to understand systems where each observation comprises measurements of two different variables, x and y using approaches of bivariate statistics.
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Revised Multilinear Regression Equations for Prediction of Lateral Spread Displacement

Journal of Geotechnical and Geoenvironmental Engineering, 2002
In 1992 and 1995, Bartlett and Youd introduced empirical equations for the prediction of lateral spread displacement; these equations have gained wide use in engineering practice. The equations were developed from the multilinear regression (MLR) of a large case history database. This study corrects and updates the original analysis.
T. Leslie Youd, Corbett M. Hansen, Steven F. Bartlett   +2 more
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Predictive population behavior analysis from multiple contexts with multilinear poisson regression

Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2018
Predicting behaviors of a population from location-oriented log data from smartphones, i.e., urban population dynamics, has become more common in mobile and pervasive computing. A bilinear representation approach has been proposed to improve the prediction accuracy of urban population dynamics by adding contexts such as geographical information and day
Masamichi Shimosaka, Takeshi Tsukiji, Hideyuki Wada, Kota Tsubouchi   +3 more
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The Use of Multilinear Regression Models in Patterned Waterfloods: Physical Meaning of the Regression Coefficients

2005
One of the reservoirs engineer's mission is to predict the behavior of hydrocarbon producing assets. Once this ability is developed he/she will try to manage tbe ''today" to maximize the future economic return of the asset. However, the techniques to predict future performance vary from an educated guess of an appropriate analogy to very complex ...
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DETERMINATION OF FACTORS AFFECTING BANK PROFITS: COMPARISON OF MULTILINEAR REGRESSION AND GRADIENT BOOSTING REGRESSION METHODS

2022
Finansal sistem içerisinde, bankalar oldukça önemli bir yere sahiptir. Geleneksel işletmeler gibi bankalarda da faaliyetlerinin temel amacı sürdürülebilir şekilde kâr elde etmektir. Bankacılık sektöründe finansal veya beşerî kaynakların yönetimi doğrudan banka kârlılığını etkileyen faktörler içerisindedir.
COŞKUNER, Abdurrahman, RENÇBER, Ömer Faruk   +1 more
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Transform-Based Tensor Auto Regression for Multilinear Time Series Forecasting

2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021
Jackson Cates, Randy C. Hoover, Kyle A. Caudle, Riley Kopp, Cagri Ozdemir   +4 more
openaire   +1 more source

Mapping the spatial variability of rainfall from a physiographic-based multilinear regression: model development and application to the Southwestern Iberian Peninsula

Environmental Monitoring and Assessment, 2022
Veronica Ruiz-Ortiz, Santiago Garcia Lopez, Granja-Martins Fernando M   +2 more
exaly