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What is the interpretation for negative r squares for machine learning algorithms?

Empirical risk minimization

Regularization perspectives on support vector machines

Generalized least squares

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Negative R-squared values in machine learning algorithms indicate that the model's predictions are worse than simply using the mean value of the target variable. It suggests that the model is not able to explain any of the variability in the data and is performing poorly. This can happen when the model is underfitting the data or when there is no linear relationship between the features and the target variable. In such cases, it is important to re-evaluate the model and consider alternative approaches to improve its performance.

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Journal Article•DOI Least square regression with lp-coefficient regularization Hongzhi Tong, Di-Rong Chen, Fenghong Yang - Show less +2 more 01 Dec 2010-Neural Computation 32 Citations	The provided paper does not discuss the interpretation of negative R-squared values for machine learning algorithms.
Open access•Journal Article Applications of regularized least squares to classification problems Nicolò Cesa-Bianchi 01 Jan 2004-Lecture Notes in Computer Science 1 Citations	The provided paper does not discuss the interpretation of negative R-squares for machine learning algorithms.
Book Chapter•DOI Least Squares Classification Masashi Sugiyama 01 Jan 2016 1 Citations	The provided paper is about Least Squares Classification. However, it does not provide any information about the interpretation of negative R-squared values for machine learning algorithms.
Open access•Posted Content Shapley Decomposition of R-Squared in Machine Learning Models Nickalus Redell 26 Aug 2019-arXiv: Methodology 14 Citations	The provided paper does not discuss the interpretation of negative R-squared values for machine learning algorithms.
Journal Article•DOI High-Dimensional Least-Squares with Perfect Positive Correlation Zhiyong Huang, Ziyan Luo, Naihua Xiu - Show less +2 more 25 Aug 2019-Asia-Pacific Journal of Operational Research	The provided paper does not discuss the interpretation of negative R-squared values for machine learning algorithms.

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