The quest for the reliability of machine learning models in binary classification on tabular data
Abstract In this paper we explore the reliability of contexts of machine learning (ML) models. There are several evaluation procedures commonly used to validate a model (precision, F1 Score and others); However, these procedures are not linked to the evaluation of learning itself, but only to the nu...
Main Authors: | Vitor Cirilo Araujo Santos, Lucas Cardoso, Ronnie Alves |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-10-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-45876-9 |
Similar Items
-
Discrimination Neural Network Model for Binary Classification Tasks on Tabular Data
by: Lkhagvadorj Munkhdalai, et al.
Published: (2023-01-01) -
Investigating group distributionally robust optimization for deep imbalanced learning: a case study of binary tabular data classification.
by: Mustapha, Ismail, et al.
Published: (2023) -
Disjunctive Threshold Networks for Tabular Data Classification
by: Weijia Wang, et al.
Published: (2023-01-01) -
Feature‐based augmentation and classification for tabular data
by: Balachander Sathianarayanan, et al.
Published: (2022-09-01) -
Tabular Data Generation to Improve Classification of Liver Disease Diagnosis
by: Mohammad Alauthman, et al.
Published: (2023-02-01)