caa a22 4500 60551867X CHVBK 20210128100726.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s10559-015-9792-z doi (NATIONALLICENCE)springer-10.1007/s10559-015-9792-z Soloshenko O. National Technical University of Ukraine "Kyiv Polytechnic Institute”, Kyiv, Ukraine aut Generalizations of Logistic Regression, Weight of Evidence, and the Gini Index for a Continuous Target Variable Taking on Probabilistic Values [Elektronische Daten] [O. Soloshenko] The author proposes original tools for improving formulas of the maximum likelihood estimation method for logistic regression, the weight of evidence formula including the information value indicator formula, and the Gini index with a view to providing the use of a continuous target variable assuming probabilistic values. The approach to the pursuance of this research consists of the application of continuous weight functions meeting certain conditions to evaluate a generalized logarithm of the likelihood function including its generalized gradient vector and generalized Hessian matrix and also the application of probability theory to generalize weight of evidence and the Gini index. Springer Science+Business Media New York, 2015 logistic regression nationallicence weight of evidence nationallicence Gini index nationallicence maximum likelihood method nationallicence credit scoring nationallicence reject inference nationallicence Cybernetics and Systems Analysis Springer US; http://www.springer-ny.com 51/6(2015-11-01), 992-1004 1060-0396 51:6<992 2015 51 10559 https://doi.org/10.1007/s10559-015-9792-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10559-015-9792-z text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Soloshenko O. National Technical University of Ukraine "Kyiv Polytechnic Institute”, Kyiv, Ukraine aut NATIONALLICENCE 773 0- Cybernetics and Systems Analysis Springer US; http://www.springer-ny.com 51/6(2015-11-01), 992-1004 1060-0396 51:6<992 2015 51 10559