Abstract: Recently, the adoption of deep learning models in several domains and for various tasks has increased, correspondingly amplifying the number of model layers and parameters needed to achieve ...
Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...
Background: Sprint interval training (SIT) is an increasingly popular time-efficient training paradigm; however, its acute impact on the immune system remains ambiguous due to inconsistent findings ...
Abstract: This article proposes an algorithm for solving multivariate regression and classification problems using piecewise linear predictors over a polyhedral partition of the feature space. The ...
Quadratic regression extends linear regression by adding squared terms and pairwise interaction terms, enabling the model to capture non-linear structure and predictor interactions. The article ...
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