Monotone Functions and Expert Models for Explanation of Machine Learning Models
There are significant difficulties for the acceptance of black-box Machine Learning (ML) models by subject matter experts (SMEs) despite significant achievements of many black-box models. A promising way to address this problem is by building a trustable, qualitative, interpretable models for the ta...
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          | Published in | Proceedings / International Conference on Information Visualisation pp. 1 - 9 | 
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| Main Authors | , | 
| Format | Conference Proceeding | 
| Language | English | 
| Published | 
            IEEE
    
        22.07.2024
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 2375-0138 | 
| DOI | 10.1109/IV64223.2024.00048 | 
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| Summary: | There are significant difficulties for the acceptance of black-box Machine Learning (ML) models by subject matter experts (SMEs) despite significant achievements of many black-box models. A promising way to address this problem is by building a trustable, qualitative, interpretable models for the task based on SME knowledge. Such qualitative models can work as qualitative explainers of black-box models or as sanity checks for them. In this paper, qualitative models operate with ordinal attributes, which can be Boolean or k-valued attributes with a small k . Humans easier understand and reason with such attributes that with continuous numeric attributes with many more values. Some ML tasks do not have sufficient training data. Building qualitative models with a SME ("expert models") is a way to solve these tasks solely with a SME's knowledge. The proposed Monotone Ordinal Expert Knowledge Acquisition (MOEKA) system allows building "expert models" through interview phases with the SME. Monotonicity is a key property of the system that is tested and used to shorten the interview process with a SME along with new methods for selecting the order of questions. MOEKA rather directly approximates domain knowledge in contrast with other ML explainers, which approximate black-box ML models. MOEKA can be also used as a method of database searching. Several case studies on gout, diabetes, and housing demonstrate efficiency of MOEKA. | 
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| ISSN: | 2375-0138 | 
| DOI: | 10.1109/IV64223.2024.00048 |