Examining the utility of nonlinear machine learning approaches versus linear regression for predicting body image outcomes: The U.S. Body Project I

Liang, Dehua; Frederick, David A.; Lledo, Elia E; Rosenfield, Natalia Stewart; Berardi, Vincent; Linstead, Erik; Maoz, Uri

doi:10.1016/j.bodyim.2022.01.013

Cited by 37 publications

(13 citation statements)

References 77 publications

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“…By analyzing the problem, determining the loss function or utility function of the problem and obtaining a model for machine learning by optimizing the loss function or utility function, this is the general set of parametric learning algorithms [ 34 , 35 ].…”

Section: Modeling Methodsmentioning

confidence: 99%

Analysis of the Stage Performance Effect of Environmental Protection Music and Dance Drama Based on Artificial Intelligence Technology

Zeng

2022

Journal of Environmental and Public Health

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There are a lot of environmental protection musicals and dances in public entertainment life to support the concept of environmental protection and to entice people to support the cause of environmental protection. As we all know, in a musical performance, the distance between the audience and the actors, the design of the stage environment, the training of the actors, the costumes of the actors, the makeup of the actors, and the musical accompaniment will all have more or less influence on the stage performance effects. In order to make environmental protection music and dance dramas profoundly meaningful to social production and human activities, it is especially important to analyze the stage performance of such music and dance dramas. The analysis of stage performance effects is not only beneficial to making the ideas spread by the music and dance drama penetrate into people’s hearts but can also provide guiding suggestions for the production of music and dance drama. Therefore, this paper proposes a linear regression algorithm based on artificial intelligence to deeply explore and analyze the influence of the above six factors on the stage performance effects of environmental protection music and dance drama. In our method, first we preprocess the data collected by classification to remove the odd values from the data so that the various types of data conform to a normal distribution. Secondly, we obtained linear fit plots of the six factors with the stage performance effect scores by using a linear regression algorithm to deeply analyze the correlation between various types of data and the stage performance effect scores. Finally, through numerical calculations, we found that the distance between the audience and the actors, the training of the actors, and the musical accompaniment have a greater influence on the performance effect of the musical cabaret in the environmental protection category. Meanwhile, the costumes of the actors, the makeup of the actors, and the design of the stage environment have less influence on the performance effect of the musical cabaret. Therefore, in the production and performance of environmental protection music and dance dramas, producers and performers should pay more attention to the distance between the audience and the actors, the design of musical accompaniment, and the training of actors. To sum up, this paper has made a scientific, detailed, and reasonable analysis of the performance effect of environmental protection music and dance dramas on stage, contributing to the dissemination of environmental protection ideas.

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Section: Modeling Methodsmentioning

confidence: 99%

Analysis of the Stage Performance Effect of Environmental Protection Music and Dance Drama Based on Artificial Intelligence Technology

Zeng

2022

Journal of Environmental and Public Health

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“…If the rowing has not been analyzed for many times, the relevant preventive measures will be eliminated. Multivariate regression will continue to analyze other prevention measures [ 10 ], and according to formulas ( 1 )~( 4 ), a new cause analysis of sports injuries will be carried out [ 11 ].…”

Section: Related Conceptsmentioning

confidence: 99%

“…The specific combination is as follows. (1) The damage cause analysis measures of information characteristics, as shown in Formula (11).…”

Section: Mathematical Model Of Multiple Regression Use the Combined M...mentioning

confidence: 99%

Research on Injury Causes and Prevention Effect of College Rowing Athletes Based on Multiple Regression and Residual Algorithm

2022

Journal of Environmental and Public Health

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Rowing competition in colleges and universities is an international competition, and it is also a favorite competition for college students. However, in the course of rowing competition, the stability of athletes’ injuries often occurs, which is difficult to solve effectively. Aiming at the problem that the loss of athletes in rowing competition in colleges and universities cannot be accurately prevented, this paper puts forward a multiple regression prevention effect model and makes a comprehensive analysis combined with complex reasons. Through the integration of multiple regression and residual analysis, we can better find out the influencing factors, aiming at finding out the causes of athletes’ injuries and putting forward corresponding countermeasures. First of all, analyze the causes of loss, establish a framework of injury prevention for college rowers, and the overall diagnosis framework is reasonable. Then, according to the “University Rowing Prevention and Control Standards” divided into various prevention measures, through the comprehensive prevention and control measure mechanism to get the cause of injury, finally, the optimal combination of various control measures forms a control system. The results of MATLAB show that the combination of multiple regression and residual analysis can improve the accuracy of athletes’ injury prevention and treatment, make the accuracy more than 90%, shorten the diagnosis time less than 10 minutes, and meet the requirements of athletes’ injury diagnosis under normal rowing competition.

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“…The regression in which the predictor and response variable has a non-linear relationship is known as non-linear regression (Liang et al, 2022). Since most relationships in G.I.S.…”

Section: Non-linear Regressionmentioning

confidence: 99%

Machine Learning Application in G.I.S. and Remote Sensing: An Overview

Upreti¹

2022

Preprint

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Machine learning (ML) is a subdivision of artificial intelligence in which the machine learns from machine-readable data and information. It uses data, learns the pattern and predicts the new outcomes. Its popularity is growing because it helps to understand the trend and provides a solution that can be either a model or a product. Applications of ML algorithms have increased drastically in G.I.S. and remote sensing in recent years. It has a broad range of applications, from developing energy-based models to assessing soil liquefaction to creating a relation between air quality and mortality. Here, in this paper, we discuss the most popular supervised ML models (classification and regression) in G.I.S. and remote sensing. The motivation for writing this paper is that ML models produce higher accuracy than traditional parametric classifiers, especially for complex data with many predictor variables. This paper provides a general overview of some popular supervised non-parametric ML models that can be used in most of the G.I.S. and remote sensing-based projects. We discuss classification (Naïve Bayes (NB), Support Vector Machine (SVM), Random Forest (RF), Decision Trees (DT)) and regression models (Random Forest (RF), Support Vector Machine (SVM), Linear and Non-Linear) here. Therefore, the article can be a guide to those interested in using ML models in their G.I.S. and remote sensing-based projects

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Examining the utility of nonlinear machine learning approaches versus linear regression for predicting body image outcomes: The U.S. Body Project I

Cited by 37 publications

References 77 publications

Analysis of the Stage Performance Effect of Environmental Protection Music and Dance Drama Based on Artificial Intelligence Technology

Analysis of the Stage Performance Effect of Environmental Protection Music and Dance Drama Based on Artificial Intelligence Technology

Research on Injury Causes and Prevention Effect of College Rowing Athletes Based on Multiple Regression and Residual Algorithm

Machine Learning Application in G.I.S. and Remote Sensing: An Overview

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