The ever-increasing number of wind farms has brought both challenges and opportunities in
the development of wind power forecasting techniques to take advantage of …

Abstract The Naïve Bayes has proven to be a tractable and efficient method for classification
in multivariate analysis. However, features are usually correlated, a fact that violates the …

Many real-life applications consider nominal categorical predictor variables that have a
hierarchical structure, eg economic activity data in Official Statistics. In this paper, we focus …

Feature Selection is a crucial procedure in Data Science tasks such as Classification, since
it identifies the relevant variables, making thus the classification procedures more …

Since the seminal paper by Bates and Granger in 1969, a vast number of ensemble
methods that combine different base regressors to generate a unique one have been …

Time-stamped cross-sectional data, which lack linkage across time points, are commonly
generated in single-cell transcriptional profiling. Many previous methods for inferring gene …

This article presents the development of a geo-visualization tool, which provides police
officers or any other type of law enforcement officer with the ability to conduct the …

Short-term load forecasting is a key task for planning and stability of the current and future
distribution grid, as it can significantly contribute to the management of energy market for …

Clustering techniques are powerful tools commonly used in statistical learning and data
analytics. Most of the past research formulates clustering tasks as a non-convex problem …

Given the increasing amounts of data and high feature dimensionalities in forecasting
problems, it is challenging to build regression models that are both computationally efficient …