Faculty, Staff and Student Publications
Publication Date
1-1-2023
Journal
Frontiers in Oncology
Abstract
One of the core elements of Machine Learning (ML) is statistics and its embedded foundational rules and without its appropriate integration, ML as we know would not exist. Various aspects of ML platforms are based on statistical rules and most notably the end results of the ML model performance cannot be objectively assessed without appropriate statistical measurements. The scope of statistics within the ML realm is rather broad and cannot be adequately covered in a single review article. Therefore, here we will mainly focus on the common statistical concepts that pertain to supervised ML (i.e. classification and regression) along with their interdependencies and certain limitations.
Keywords
Machine Learning, statistics, regression, classification, model evaluations, artificial intelligence
DOI
10.3389/fonc.2023.1130229
PMID
36845729
PMCID
PMC9949554
PubMedCentral® Posted Date
February 2023
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes