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Monotonic classification: An overview on algorithms, performance measures and data sets
- Source :
- Neurocomputing. 341:168-182
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Currently, knowledge discovery in databases is an essential first step when identifying valid, novel and useful patterns for decision making. There are many real-world scenarios, such as bankruptcy prediction, option pricing or medical diagnosis, where the classification models to be learned need to fulfill restrictions of monotonicity (i.e. the target class label should not decrease when input attributes values increase). For instance, it is rational to assume that a higher debt ratio of a company should never result in a lower level of bankruptcy risk. Consequently, there is a growing interest from the data mining research community concerning monotonic predictive models. This paper aims to present an overview of the literature in the field, analyzing existing techniques and proposing a taxonomy of the algorithms based on the type of model generated. For each method, we review the quality metrics considered in the evaluation and the different data sets and monotonic problems used in the analysis. In this way, this paper serves as an overview of monotonic classification research in specialized literature and can be used as a functional guide for the field.
- Subjects :
- FOS: Computer and information sciences
Computer Science - Machine Learning
0209 industrial biotechnology
Computer Science - Artificial Intelligence
Computer science
Cognitive Neuroscience
media_common.quotation_subject
Monotonic function
02 engineering and technology
Machine learning
computer.software_genre
Field (computer science)
Machine Learning (cs.LG)
020901 industrial engineering & automation
Knowledge extraction
Artificial Intelligence
Taxonomy (general)
0202 electrical engineering, electronic engineering, information engineering
Quality (business)
Medical diagnosis
media_common
business.industry
Class (biology)
Computer Science Applications
Data set
Artificial Intelligence (cs.AI)
Valuation of options
Bankruptcy prediction
020201 artificial intelligence & image processing
Artificial intelligence
business
computer
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 341
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi.dedup.....1fc47738256358aca4061e04b0d09df2