AUTHOR=Rashidi Hooman H. , Albahra Samer , Robertson Scott , Tran Nam K. , Hu Bo TITLE=Common statistical concepts in the supervised Machine Learning arena JOURNAL=Frontiers in Oncology VOLUME=13 YEAR=2023 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1130229 DOI=10.3389/fonc.2023.1130229 ISSN=2234-943X 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.