SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENT
The problem considered in this article involves the construction of evaluation model, which could subsequently be used in the fieldof modeling and risk management. The research work is finalizedby a construction of a new model on the basis of observa-tions of the models used for risk management and...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Lublin University of Technology
2014-06-01
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| Series: | Advances in Sciences and Technology |
| Subjects: | |
| Online Access: | http://www.journalssystem.com/astrj/Self-learning-scoring-models-introduction-of-an-on-line-approach-to-risk-assesment,231,0,2.html |
| _version_ | 1811326819615375360 |
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| author | Ryszard Kozera Przemyslaw Koziol |
| author_facet | Ryszard Kozera Przemyslaw Koziol |
| author_sort | Ryszard Kozera |
| collection | DOAJ |
| description | The problem considered in this article involves the construction of evaluation model, which could subsequently be used in the fieldof modeling and risk management. The research work is finalizedby a construction of a new model on the basis of observa-tions of the models used for risk management and knowledge of information theory, machine learning and artificialneural networks. The developed tools are trained on-line, using their ability for automatic deduction rules based on data, during model application for evaluation tasks. The model, consequently changes the data analysis stage, limits the scope of the necessary expertise in the area, where the assessment model can be used and, to some extent, the shape of the model becomes independent from the current range of available data. These features increase its ability to general-ize and to cope with the data of previously undefinedclasses, as well as improve its resistance to gaps occurring in the data. Performance of the model presented in this paper is tested and verifiedon the basis of real-life data, which would resemble a potentially real practical application. Preliminary tests performed within the scope of this work indicate that the developed model can form a starting point for further research as some of the used mechanisms have a fairly high efficiency and flexibility. |
| first_indexed | 2024-04-13T14:55:15Z |
| format | Article |
| id | doaj.art-57e05471b1a74ac288e705cf154376ab |
| institution | Directory Open Access Journal |
| issn | 2080-4075 2299-8624 |
| language | English |
| last_indexed | 2024-04-13T14:55:15Z |
| publishDate | 2014-06-01 |
| publisher | Lublin University of Technology |
| record_format | Article |
| series | Advances in Sciences and Technology |
| spelling | doaj.art-57e05471b1a74ac288e705cf154376ab2022-12-22T02:42:27ZengLublin University of TechnologyAdvances in Sciences and Technology2080-40752299-86242014-06-01822425010.12913/22998624.1105164231SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENTRyszard Kozera0Przemyslaw Koziol1Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences (SGGW), Nowoursynowska 159, 02-776 Warsaw, PolandFaculty of Mathematics and Information, Warsaw University of Technology, PL Politechniki 1, 00-661 Warsaw, PolandThe problem considered in this article involves the construction of evaluation model, which could subsequently be used in the fieldof modeling and risk management. The research work is finalizedby a construction of a new model on the basis of observa-tions of the models used for risk management and knowledge of information theory, machine learning and artificialneural networks. The developed tools are trained on-line, using their ability for automatic deduction rules based on data, during model application for evaluation tasks. The model, consequently changes the data analysis stage, limits the scope of the necessary expertise in the area, where the assessment model can be used and, to some extent, the shape of the model becomes independent from the current range of available data. These features increase its ability to general-ize and to cope with the data of previously undefinedclasses, as well as improve its resistance to gaps occurring in the data. Performance of the model presented in this paper is tested and verifiedon the basis of real-life data, which would resemble a potentially real practical application. Preliminary tests performed within the scope of this work indicate that the developed model can form a starting point for further research as some of the used mechanisms have a fairly high efficiency and flexibility.http://www.journalssystem.com/astrj/Self-learning-scoring-models-introduction-of-an-on-line-approach-to-risk-assesment,231,0,2.htmlrisk managementscoring modelinformation theory |
| spellingShingle | Ryszard Kozera Przemyslaw Koziol SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENT Advances in Sciences and Technology risk management scoring model information theory |
| title | SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENT |
| title_full | SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENT |
| title_fullStr | SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENT |
| title_full_unstemmed | SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENT |
| title_short | SELF-LEARNING SCORING MODELS – INTRODUCTION OF AN ON-LINE APPROACH TO RISK ASSESMENT |
| title_sort | self learning scoring models introduction of an on line approach to risk assesment |
| topic | risk management scoring model information theory |
| url | http://www.journalssystem.com/astrj/Self-learning-scoring-models-introduction-of-an-on-line-approach-to-risk-assesment,231,0,2.html |
| work_keys_str_mv | AT ryszardkozera selflearningscoringmodelsintroductionofanonlineapproachtoriskassesment AT przemyslawkoziol selflearningscoringmodelsintroductionofanonlineapproachtoriskassesment |