Recently, a class of machine learning-inspired procedures, termed kernel machine methods, has been extensively developed in the statistical literature. In this note, we construct a so-called ‘adaptively minimax’ kernel machine. Such a construction highlights the limits on the...

The training of Support Vector Machines may be a very difficult task when dealing with very large datasets. The memory requirement and the time consumption of the SVMs algorithms grow rapidly with the increase of the data. To overcome these drawbacks a lot of parallel algorithms have been...

Miombo woodlands in Southern Africa are experiencing accelerated changes due to natural and anthropogenic disturbances. In order to formulate sustainable woodland management strategies in the Miombo ecosystem, timely and up-to-date land cover information is required. Recent advances in remote...

Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the...

Developing new methods for predictive modeling of time series and application of the existing techniques in other areas will be a permanent concern for both researchers and companies that are interested in gaining competitive advantages. In this paper I present the construction of an artificial...

Learning from imbalanced data, where the number of observations in one class is significantly larger than the ones in the other class, has gained considerable attention in the machine learning community. Assuming the difficulty in predicting each class is similar, most standard classifiers will...

Rock burst is one of the common failures in hard rock mining and civil construction. This study focuses on the prediction of rock burst classification with case instances using cloud models and attribution weight. First, cloud models are introduced briefly related to the rock burst...

Combined simulation-optimization models have been widely used to address the management of water resources issues. This paper presents a simulation-optimization model for conjunctive use of surface water and groundwater at a basin-wide scale, the Zayandehrood river basin in west central Iran. In...

CRM gains increasing importance due to intensive competition and saturated markets. With the purpose of retaining customers, academics as well as practitioners find it crucial to build a churn prediction model that is as accurate as possible. This study applies support vector machines in a...

In this paper we propose an approach to predict insolvency of non-life insurance companies based on the application of Support Vector Machines (SVMs), hybridized with two global search heuristics: a Genetic Algorithm (GA) and a Simulated Annealing (SA). A SVM is used to classify firms as failed...