Results 161 to 170 of about 15,675 (200)

Multilinear regression analysis of antiviral medications with topological indices

Journal of Molecular Graphics and Modelling
Topological indices are effective tools for modeling and predicting the molecular structure and physicochemical properties of medications, eliminating the need for lengthy laboratory procedures. Topological indices offer the benefit of acting as fundamental numerical indicators in models related to quantitative structure-property relationships (QSPR ...
Selvarani P
exaly   +3 more sources

Prediction of bioactivity of ACAT2 inhibitors by multilinear regression analysis and support vector machine

Bioorganic and Medicinal Chemistry Letters, 2013
Two quantitative structure-activity relationships (QSAR) models for predicting 95 compounds inhibiting Acyl-coenzyme A: cholesterol acyltransferase2 (ACAT2) were developed. The whole data set was randomly split into a training set including 72 compounds and a test set including 23 compounds.
Aixia Yan, Bin Dai
exaly   +3 more sources

Multilinear Jointly Sparse Robust Discriminant Regression

Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition, 2020
Tensor data, such as image, video, etc. is drawing more and more attention from researchers. Therefore, in this paper, we will focus on the tensor data, proposing a novel tensor-based feature extraction model. Previously, Lai et al. proposed Robust Discriminant Regression (RDR) by using L2, 1 -norm as basic metric to improve the robustness of model ...
Zhuozhen Yu, Zhihui Lai 0001, Yusheng Lai   +2 more
openaire   +1 more source

Correct and incorrect use of multilinear regression

Chemometrics and Intelligent Laboratory Systems, 1995
Abstract Multilinear regression is applied when experimenters wish to investigate the relationship between a block of predictor variables ( X ), whose values are fixed by the experimenter, and one or more responses ( Y ), measured at each experiment.
M. Sergent, D. Mathieu, R. Phan Tan Luu, DRAVA, GIULIANA   +3 more
openaire   +3 more sources

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
openaire   +1 more source

Further Multilinear Regression

2010
For one regressor x, simple linear regression is fine for fitting straight-line trends. But what about more general trends – quadratic trends, for example? (E.g. height against time for a body falling under gravity is quadratic.) Or cubic trends? (E.g.: the van der Waals equation of state in physical chemistry.) Or quartic? – etc.
N. H. Bingham, John M. Fry
openaire   +1 more source

Multilinear Regression for Embedded Feature Selection with Application to fMRI Analysis

Proceedings of the AAAI Conference on Artificial Intelligence, 2017
Embedded feature selection is effective when both prediction and interpretation are needed. The Lasso and its extensions are standard methods for selecting a subset of features while optimizing a prediction function. In this paper, we are interested in embedded feature selection for multidimensional data, wherein (1) there is no need to
Xiaonan Song, Haiping Lu
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +3 more sources

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
openaire   +1 more source