PMID- 37303478
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230928
IS  - 2196-1115 (Print)
IS  - 2196-1115 (Electronic)
IS  - 2196-1115 (Linking)
VI  - 10
IP  - 1
DP  - 2023
TI  - Framework for multi-criteria assessment of classification models for the purposes 
      of credit scoring.
PG  - 94
LID - 10.1186/s40537-023-00768-7 [doi]
LID - 94
AB  - The main dilemma in the case of classification tasks is to find-from among many 
      combinations of methods, techniques and values of their parameters-such a 
      structure of the classifier model that could achieve the best accuracy and 
      efficiency. The aim of the article is to develop and practically verify a 
      framework for multi-criteria evaluation of classification models for the purposes 
      of credit scoring. The framework is based on the Multi-Criteria Decision Making 
      (MCDM) method called PROSA (PROMETHEE for Sustainability Analysis), which brought 
      added value to the modelling process, allowing the assessment of classifiers to 
      include the consistency of the results obtained on the training set and the 
      validation set, and the consistency of the classification results obtained for 
      the data acquired in different time periods. The study considered two aggregation 
      scenarios of TSC (Time periods, Sub-criteria, Criteria) and SCT (Sub-criteria, 
      Criteria, Time periods), in which very similar results were obtained for the 
      evaluation of classification models. The leading positions in the ranking were 
      taken by borrower classification models using logistic regression and a small 
      number of predictive variables. The obtained rankings were compared to the 
      assessments of the expert team, which turned out to be very similar.
CI  - (c) The Author(s) 2023.
FAU - Ziemba, Pawel
AU  - Ziemba P
AD  - Institute of Management, University of Szczecin, Szczecin, Poland. GRID: 
      grid.79757.3b. ISNI: 0000 0000 8780 7659
FAU - Becker, Jaroslaw
AU  - Becker J
AD  - Faculty of Technology, The Jacob of Paradies University, Gorzow Wielkopolski, 
      Poland. GRID: grid.498902.e. ISNI: 0000 0004 5940 857X
FAU - Becker, Aneta
AU  - Becker A
AD  - Faculty of Economics, West Pomeranian University of Technology, Szczecin, Poland. 
      GRID: grid.411391.f. ISNI: 0000 0001 0659 0011
FAU - Radomska-Zalas, Aleksandra
AU  - Radomska-Zalas A
AD  - Faculty of Technology, The Jacob of Paradies University, Gorzow Wielkopolski, 
      Poland. GRID: grid.498902.e. ISNI: 0000 0004 5940 857X
LA  - eng
PT  - Journal Article
DEP - 20230602
PL  - Germany
TA  - J Big Data
JT  - Journal of big data
JID - 101659495
PMC - PMC10237068
OTO - NOTNLM
OT  - Classification algorithms
OT  - Credit scoring
OT  - Model evaluation
OT  - Multi-criteria decision making
OT  - PROMETHEE II
OT  - PROSA
COIS- Competing interestsThe authors declare no competing interests.
EDAT- 2023/06/12 06:42
MHDA- 2023/06/12 06:43
PMCR- 2023/06/02
CRDT- 2023/06/12 03:54
PHST- 2022/08/25 00:00 [received]
PHST- 2023/05/17 00:00 [accepted]
PHST- 2023/06/12 06:43 [medline]
PHST- 2023/06/12 06:42 [pubmed]
PHST- 2023/06/12 03:54 [entrez]
PHST- 2023/06/02 00:00 [pmc-release]
AID - 768 [pii]
AID - 10.1186/s40537-023-00768-7 [doi]
PST - ppublish
SO  - J Big Data. 2023;10(1):94. doi: 10.1186/s40537-023-00768-7. Epub 2023 Jun 2.