Dengue prediction in Latin America using machine learning and the one health perspective: a literature review

M Cabrera, J Leake, J Naranjo-Torres… - Tropical Medicine and …, 2022 - mdpi.com
Dengue fever is a serious and growing public health problem in Latin America and
elsewhere, intensified by climate change and human mobility. This paper reviews the …

The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation

D Chicco, MJ Warrens, G Jurman - Peerj computer science, 2021 - peerj.com
Regression analysis makes up a large part of supervised machine learning, and consists of
the prediction of a continuous independent target from a set of other predictor variables. The …

Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology

A Botchkarev - arXiv preprint arXiv:1809.03006, 2018 - arxiv.org
Performance metrics (error measures) are vital components of the evaluation frameworks in
various fields. The intention of this study was to overview of a variety of performance metrics …

Investigation of performance metrics in regression analysis and machine learning-based prediction models

V Plevris, G Solorzano, NP Bakas… - … Methods in Applied …, 2022 - oda.oslomet.no
Performance metrics (Evaluation metrics or error metrics) are crucial components of
regression analysis and machine learning-based prediction models. A performance metric …

A new typology design of performance metrics to measure errors in machine learning regression algorithms

A Botchkarev - Interdisciplinary Journal of Information …, 2019 - informingscience.org
Aim/Purpose: The aim of this study was to analyze various performance metrics and
approaches to their classification. The main goal of the study was to develop a new typology …

Biomarker-informed machine learning model of cognitive fatigue from a heart rate response perspective

KFA Lee, WS Gan, G Christopoulos - Sensors, 2021 - mdpi.com
Cognitive fatigue is a psychological state characterised by feelings of tiredness and
impaired cognitive functioning arising from high cognitive demands. This paper examines …

A machine learning-based model to estimate PM2. 5 concentration levels in Delhi's atmosphere

S Kumar, S Mishra, SK Singh - Heliyon, 2020 - cell.com
During the last many years, the air quality of the capital city of India, Delhi had been
hazardous. A large number of people have been diagnosed with Asthma and other …

Machine learning model for predicting structural response of RC slabs exposed to blast loading

MK Almustafa, ML Nehdi - Engineering Structures, 2020 - Elsevier
Considering the risk of exposure of diverse structures to detonations and explosions, the
need for understanding the structural behavior under such events and enhancing blast …

Prediction of the electricity generation of a 60-kW photovoltaic system with intelligent models ANFIS and optimized ANFIS-PSO

LO Lara-Cerecedo, JF Hinojosa, N Pitalúa-Díaz… - Energies, 2023 - mdpi.com
The development and constant improvement of accurate predictive models of electricity
generation from photovoltaic systems provide valuable planning tools for designers …

Neurodegenerative disease detection and severity prediction using deep learning approaches

ÇB Erdaş, E Sümer, S Kibaroğlu - Biomedical Signal Processing and …, 2021 - Elsevier
Neurodegenerative diseases (NDDs) such as amyotrophic lateral sclerosis (ALS),
Huntington's disease (HD), and Parkinson's disease (PD) can manifest themselves …