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Enhancing heart disease prediction using gaussian process regression and sequential analysis for optimal sampling efficiencyHeart disease poses a significant risk to global health, and accurate prediction of this risk
A new approach to the mathematical modelling of econometric dynamics of enterprises’ demand for labor at an industrial enterprise, in particular, we develop: i) a linear regression model to define the dependence
Generalized Embedding Regression: A Framework for Supervised Feature Extraction performance in recognition tasks. In this article, a framework called generalized embedding regression (GER
WORLD SOYBEAN MARKET IN THE VIEW OF REGIONAL FOOD SECURITY (LATE XX - EARLY XXI CENTURY) market problem allows us to make a forecast as to the progressive and regressive ways of food security
Outlier filtering in a sampleThe problem of filtering outliers in the sample is considered. A genetic algorithm for outlier
Thermally induced diphenylalanine cyclization in solid phase phase under heating was studied, which is a stage in formation of various nanostructures from
Estimation of the Mean Value for the Normal Distribution with Constraints on d-Risk© 2018, Pleiades Publishing, Ltd. We consider the problem of an estimation of the mean value
Calibration of 2-D soil zymography for correct analysis of enzyme distribution developed a new calibration approach that is based on a piecewise linear regression. The new approach
Using machine learning algorithms to develop a web application for predicting prices on the stock market in the financial sector. The article discusses the possibility of using linear regression models when developing a
Evolutional methods for creating artificial intelligence of robotic technical systemsThis paper considers evolutionary methods of symbolic regression for the creation of artificial
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