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As the size, complexity, and availability of data continues to grow, scientists are increasingly relying upon black-box learning algorithms that can often provide accurate predictions with minimal a priori model specifications. Tools like random forests ...

Throughout the last decade, random forests have established themselves as among the most accurate and popular supervised learning methods. While their black-box nature has made their mathematical analysis difficult, recent work has established important ...

Latent Autoimmune Diabetes in Adults (LADA) is a condition, which is rarely recognised as a complex disease within its own right and remains under researched. Completely over-shadowed by Type 1 and Type 2 diabetes, LADA is the second most prevalent genre ...

Feature selection is an essential pre-processing step in data mining. It aims at identifying the highly predictive feature subset out of a large set of candidate features. Several approaches for feature selection have been proposed in the ...

Due to the intricacies surrounding taste profiles, one's view of good wine is subjective. Therefore, it is advantageous to provide a more objective, data‐driven way to assess wine preferences. Motivated by a previous study that modeled wine ...

Feature selection identifies the key aspects involved in predicting the outcome. In this study, we propose boruta and elastic net (Enet) feature selection for classifying breast cancer datasets. A comparative study of boruta, Enet along with genetic ...

In a recent paper Gromping provided a wide‐ranging review of metrics for assessing variable importance in regression analysis. There are, however, several flaws in Gromping's criticism of the well‐known metric attributed to Pratt. Among the metrics she ...

What is the most important predictor? Easy to assess if predictors are unrelated (left). Not so easy to assess if predictors are related (right). image image

Feature selection is an important process within machine learning problems. Through pressures imposed on models during evolution, genetic programming performs basic feature selection, and so analysis of the evolved models can provide some insights into ...

In many online advertising campaigns, multiple vendors, publishers or search engines (herein called channels) are contracted to serve advertisements to internet users on behalf of a client seeking specific types of conversion. In such campaigns, ...

Variations in offset print quality relate to numerous parameters of printing press and paper. To maintain constant quality of products, press operators need to assess, explore and monitor print quality. This paper presents a novel system for assessing ...

Feature selection in high-dimensional data sets is an open problem with no universal satisfactory method available. In this paper we discuss the requirements for such a method with respect to the various aspects of feature importance and explore them ...

Precision Agriculture applies state-of-the-art GPS technology in connection with site-specific, sensor-based crop management. It can also be described as a data-driven approach to agriculture, which is strongly connected with a number of data mining ...