Feature selection plays an important role in the successful application of machine learning techniques to large real-world datasets. Avoiding model overfitting, especially when the number of features far exceeds the number of observations, requires selecting informative features and/or...

A technique based on rough set theory is investigated for identifying defects on a backlight (a rear window of a vehicle with a defrost circuit). Since replacement of defective backlights result in a significant financial loss, automobile manufacturers are trying to remove defective backlights...

Purpose – This study aims to present an empirical model designed to forecast bank credit ratings using only quantitative and publicly available information from their financial statements. For this reason, the authors use the long-term ratings provided by Fitch in 2012. The sample consists of...

The paper deals with a modeling procedure which aims to predict the power output of wind farm electricity generators. The following modeling steps are proposed: factor selection, raw data pretreatment, model evaluation and optimization. Both heuristic and formal methods are combined to construct...

A way to achieve feature selection for classification problems polluted by label noise is proposed. The performances of traditional feature selection algorithms often decrease sharply when some samples are wrongly labelled. A method based on a probabilistic label noise model combined with a...

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are...

Empirical modeling of the industrial antibiotic fed-batch fermentation process is discussed in this paper. Several methods including neural networks, genetic algorithms and feature selection are combined with prior knowledge in the research methodology. A linear model, a radial basis function...

Although support vector regression models are being used successfully in various applications, the size of the business datasets with millions of observations and thousands of variables makes training them difficult, if not impossible to solve. This paper introduces the Row and Column Selection...

This paper introduces a new hybrid bio-inspired solver which combines elements from the recently proposed Coral Reefs Optimization (CRO) algorithm with operators from the Harmony Search (HS) approach, which gives rise to the coined CRO-HS optimization technique. Specifically, this novel...

The aim of this study was to identify some new factors that may impact the occurrence and distribution of landslides based on light detection and ranging digital elevation model (LiDAR DEM), and to examine whether these factors can apply to distinguish between landslide and non-landslide pixels....