This special issue aims to develop machine learning techniques of supervised analysis with continuous dependent variable and continuous independent variables, developing the regression model including the phases of identification, estimation, diagnosis and prediction. Among the types of regression models incorporated, the following stand out:Multiple linear regression modelStandard Least-Squares FitGeneralized Linear ModelsStepwise RegressionRobust RegressionRidge RegressionLasso and Elastic NetWide Data via Lasso and Parallel ComputingLasso RegularizationLasso and Elastic Net with Cross ValidationLinear Mixed-Effects ModelFit Mixed-Effects Spline Regression, Non linear multiregression and Applications.

Aims and Scope:

1. Deep learning technologies and its application
2. Artificial Intelligence Techniques on Software Engineering
3. Intelligent decision support systems
4. Big data software and applications in smart energy, smart business and smart cities
5. Smart grid using advanced machine learning
6. Data analytics