A Strategy for Predicting the Performance of Supervised and Unsupervised Tabular Data Classifiers

Abstract Machine Learning algorithms that perform classification are increasingly been adopted in Information and Communication Technology (ICT) systems and infrastructures due to their capability to profile their expected behavior and detect anomalies due to ongoing errors or intrusions. Deploying...

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Bibliographic Details

Published in:	Data Science and Engineering
Main Authors:	Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli
Format:	Article
Language:	English
Published:	SpringerOpen 2024-10-01
Subjects:	Feature ranking Anomaly detection Classification performance Machine learning Error detection
Online Access:	https://doi.org/10.1007/s41019-024-00264-9