Many prediction, decision-making, and control architectures rely on online learned Gaussian process (GP) models. However, most existing GP regression algorithms assume a single generative model, ...

This paper is a novel approach to improving the accuracy of wind power generation predictions by using linear regression (LR) algorithm differentiated with the Lasso regression (LaR). The wind power ...

It should be noted that quantile regression involves a non-differentiable optimization problem with a piecewise linear loss function, also known as the check function. Most existing quantile ...

For our PAI course project, we are building several disease prediction systems, including heart disease, diabetes, Parkinson's, and breast cancer classification. Using machine learning algorithms, we ...

dart classifier data-science machine-learning algorithm linear-regression machine-learning-algorithms regression hyperparameters sgd logistic-regression softmax-regression dartlang stochastic-gradient ...