Results 211 to 220 of about 1,298,639 (263)

Artificial Neural Network and Non-Linear Regression-Based Optimization of the Degradation of Acid Black 52 Using Atmospheric Plasma Process. [PDF]

ACS Omega
Torres C, Vergara-Sánchez J, Gómez A, Reyes PG, Martínez H, Natividad R, Regalado-Méndez A.   +6 more
europepmc   +1 more source

Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States. [PDF]

JCO Clin Cancer Inform
Hashtarkhani S, White BM, Hoseini B, Schwartz DL, Shaban-Nejad A.   +4 more
europepmc   +1 more source

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Linear regression

Wiley Interdisciplinary Reviews: Computational Statistics, 2012
Xin Yan, Chih-Ling Tsai
exaly   +2 more sources

Benign overfitting in linear regression [PDF]

Proceedings of the National Academy of Sciences of the United States of America, 2020
The phenomenon of benign overfitting is one of the key mysteries uncovered by deep learning methodology: deep neural networks seem to predict well, even with a perfect fit to noisy training data. Motivated by this phenomenon, we consider when a perfect fit to training data in linear regression is compatible with accurate prediction.
Philip Long, Peter Bartlett, Gabor Lugosi   +2 more
exaly   +7 more sources

Grouping and linear regression

Journal of Chronic Diseases, 1982
With a large number of observations, the method of grouping is often employed to provide simpler graphs or tables. When one investigates the relationship between two variables, one usually groups based on the magnitude of the independent variable, and then plots the dependent variable averages against independent variable averages to get a clearer ...
K K, Lan, M, Halperin, G T, Waldman
openaire   +2 more sources

Regression: simple linear

International Journal of Injury Control and Safety Promotion, 2018
Regression is a statistical term used for describing models that estimate the relationships among variables.
openaire   +2 more sources

Linear Regression and Logistic Regression

2023
Supervised learning is a machine learning task of mapping the input to the output on the basis of labeled input-output example pairs. Supervised learning may be of two types: classification and regression. In this chapter, we will discuss linear regression in one variable, linear regression in multiple variables, gradient descent, and polynomial ...
Deepti Chopra, Roopal Khurana
openaire   +1 more source