Linear regression is a common technique in artificial intelligence (AI) that allows you to model the relationship between a dependent variable and one or more independent variables. However, how ...

Journal reference Neurocomputing, Elsevier, 2016, Advances in artificial neural networks, machine learning and computational intelligence - Selected papers from the 23rd European Symposium on ...

Here with m = (1,1) and k = -2 the regression finds the plane 1*x + 1*y - 2 = z and essentially rejects the last mapping as an outlier.

Here with m = (1,1) and k = -2 the regression finds the plane 1*x + 1*y - 2 = z and essentially rejects the last mapping as an outlier.

The purpose of this study was to confirm the potential of XGBoost as a vascular aging assessment model based on the photoplethysmogram (PPG) features suggested in previous studies, and to explore the ...

In this paper, we exploit the properties of mean absolute error (MAE) as a loss function for the deep neural network (DNN) based vector-to-vector regression. Th ...

1. Introduction. Consider the multiple linear regression model, where. y is an n × 1 vector of values of the response variable corresponding to X, an n × k matrix of predictor variables that may ...