A New Typology Design of Performance Metrics to Measure Errors in Machine Learning Regression Algorithms
Toronto Metropolitan University · State University "Kyiv Aviation Institute"
Abstract
Aim/Purpose: The aim of this study was to analyze various performance metrics and approaches to their classification. The main goal of the study was to develop a new typology that will help to advance knowledge of metrics and facilitate their use in machine learning regression algorithms Background: Performance metrics (error measures) are vital components of the evaluation frameworks in various fields. A performance metric can be defined as a logical and mathematical construct designed to measure how close are the actual results from what has been expected or predicted. A vast variety of performance metrics have been described in academic literature. The most commonly mentioned metrics in research studies are…
Citation impact
- FWCI
- 41.36
- Percentile
- 100%
- References
- 78
Authors
1Topics & keywords
- Computer science
- Metric (unit)
- Machine learning
- Measure (data warehouse)
- Data mining
- Construct (python library)
- Mean squared error
- Artificial intelligence
- Quality Education