Search Results - subject:"Linear combination"

A new model averaging approach in predicting credit risk default

Jha, Paritosh Navinchandra; Cucculelli, Marco - In: Risks 9 (2021) 6, pp. 1-30

creating an ensemble model as a weighted linear combination of machine learning models. The idea can be generalized to any …

Persistent link: https://www.econbiz.de/10013200780

A new model averaging approach in predicting credit risk default

Jha, Paritosh Navinchandra; Cucculelli, Marco - In: Risks : open access journal 9 (2021) 6, pp. 1-30

creating an ensemble model as a weighted linear combination of machine learning models. The idea can be generalized to any …

Persistent link: https://www.econbiz.de/10012598408

Meta-search based approach for Arabic information retrieval

Ben Guirat, Souheila; Bounhas, Ibrahim; Slimani, Yahya - In: Online Information Review 46 (2022) 7, pp. 1257-1274

rank aggregation approaches which combine the results of these systems. The first approach is based on linear combination …, consistently and significantly enhances IR results. The proposed classification-based approach outperforms linear combination and …

Persistent link: https://www.econbiz.de/10014967219

New Deterministic Solution to a chance constrained linear programming model with Weibull Random Coefficients

Ismail, Maha; El-Hefnawy, Ali; Saad, Abd El-Naser - In: Future Business Journal 4 (2018) 1, pp. 109-120

Linear Programming model is an important tool used to solve constrained optimization problems. In fact, the real life problems are usually occurring in the presence of uncertainty. For instance, in managerial problems of assigning employees to different tasks with the aim of minimizing the total...

Persistent link: https://www.econbiz.de/10011937850

New Deterministic Solution to a chance constrained linear programming model with Weibull Random Coefficients

Ismail, Maha; El-Hefnawy, Ali; Saad, Abd El-Naser - In: Future Business Journal 4 (2018) 1, pp. 109-120

Persistent link: https://www.econbiz.de/10011862381

The Song rule outperforms optimal-batch-size variance estimators in simulation output analysis

Song, Wheyming Tina - In: European journal of operational research : EJOR 275 (2019) 3, pp. 1072-1082

Persistent link: https://www.econbiz.de/10011993654

Two simple algorithms on linear combination of multiple biomarkers to maximize partial area under the ROC curve

Yu, Wenbao; Park, Taesung - In: Computational Statistics & Data Analysis 88 (2015) C, pp. 15-27

diagnostic tool. Su and Liu (1993) derived the best linear combination that maximizes AUC when the markers are multivariate … under the curve (pAUC). In this paper, we propose two easy-implemented algorithms, to find the best linear combination of …

Persistent link: https://www.econbiz.de/10011264462

Empirical likelihood ratio confidence interval estimation of best linear combinations of biomarkers

Chen, Xiwei; Vexler, Albert; Markatou, Marianthi - In: Computational Statistics & Data Analysis 82 (2015) C, pp. 186-198

operating characteristic curve (AUC) to construct nonparametric confidence intervals of AUC based on the best linear combination …

Persistent link: https://www.econbiz.de/10011117709

Approximate ellipsoidal tolerance regions for multivariate normal populations

Mbodj, Malick; Mathew, Thomas - In: Statistics & Probability Letters 97 (2015) C, pp. 41-45

approximation due to Liu et al. (2008) for the cdf of a positive linear combination of independent non-central chisquare random …

Persistent link: https://www.econbiz.de/10011189365

A Comparative Study of Various Inclusive Indices and the Index Constructed by the Principal Components Analysis

Mishra, SK - Volkswirtschaftliche Fakultät, … - 2007

Construction of (composite) indices by the PCA is very common, but this method has a preference for highly correlated variables to the poorly correlated variables in the data set. However, poor correlation does not entail the marginal importance, since correlation coefficients among the...

Persistent link: https://www.econbiz.de/10005790180