2024
DOI: 10.3390/math12223623
|View full text |Cite
|
Sign up to set email alerts
|

A Novel Outlier-Robust Accuracy Measure for Machine Learning Regression Using a Non-Convex Distance Metric

Ahmad B. Hassanat,
Mohammad Khaled Alqaralleh,
Ahmad S. Tarawneh
et al.

Abstract: Regression, a supervised machine learning approach, establishes relationships between independent variables and a continuous dependent variable. It is widely applied in areas like price prediction and time series forecasting. The performance of regression models is typically assessed using error metrics such as the Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). However, these metrics present challenges including sensitivity to outliers (notably MSE and RMSE) and scale … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 42 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?