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Problem definition: Airports and airlines have been challenged to improve decision making by producing accurate forecasts in real time. We develop a two-phased predictive system that produces forecasts of transfer passenger flows at an airport. In the ...

Increasing nonresponse rates is a pressing issue for many longitudinal panel studies. Respondents frequently either refuse participation in single survey waves (temporary dropout) or discontinue participation altogether (permanent dropout). Contemporary ...

This paper examines a novel gradient boosting framework for regression. We regularize gradient boosted trees by introducing subsampling and employ a modified shrinkage algorithm so that at every boosting stage the estimate is given by an average of trees. ...

User modelling is an essential process for recommender systems. In user interests modelling, two kinds of approaches can be found. The first uses the text extracted from the user's browsing history to predict his interest degree, while the second, besides ...

The problem of dependency modeling by experimentally obtained observations is considered. The objective is to develop methods for neural network model synthesis allowing to automatize, simplify and speed-up model building. The mathematical support ...

In this article, we contribute to the longstanding challenge of how to explain the listener’s acceptability for a particular piece of music, using harmony as one of the crucial dimensions in music, one of the least examined in this context. We propose ...

Latent factor models have achieved great success in personalized recommendations, but they are also notoriously difficult to explain. In this work, we integrate regression trees to guide the learning of latent factor models for recommendation, and use ...

In the context of Web A/B testing, dynamic assignment of traffic aims to promote the best variation (A or B) as quickly as possible. However, dynamic assignment is difficult to use when the difference between A and B affects the visitor ...

Stiffness and friction are regarded as important haptic cues for designers of haptic virtual environments. One virtual concave curvature discrimination test based on randomised block design with three factors, radius, stiffness and friction, has been ...

The assessment of patient well-being is highly relevant for the early detection of diseases, for assessing the risks of therapies, or for evaluating therapy outcomes. The knowledge to assess a patient's well-being is actually tacit knowledge and thus, ...

Automatic performance tuning is becoming an increasingly valuable tool for improving performance portability when targeting diverse ranges of processor architectures. Much of the existing work to develop auto-tuning techniques focuses solely on ...

None of numerous existing traffic flow forecasting models focus on work zones. Work zone events create conditions that are different from both normal operating conditions and incident conditions. In this paper, four models were developed for forecasting ...

The climate of a region is often determined by its landscape and amount of vegetation present in it. Environment parameters such as rainfall, wind-speed and humidity are highly influenced by these alluvial features. Bangladesh, a country situated on the ...

Graphics processing units (GPUs) are in increasingly wide use, but significant hurdles lie in selecting the appropriate algorithms, runtime parameter settings, and hardware configurations to achieve power and performance goals with them. Exploring ...

Data streams are endless flow of data produced in high speed, large size and usually non-stationary environments. The main property of these streams is the occurrence of concept drifts. Using decision trees is shown to be a powerful approach for ...

In this paper we address the problem of identifying a continuous nonlinear model from a set of discrete observations. The goal is to build a compact and accurate model of an underlying process, which is interpretable by the user, and can be also used ...

By focusing on sovereign defaults, this paper introduces a multidimensional distance-to-collapse point based on a two-step procedure. The first step is nonparametric and provides an early warning system that signals a potential crisis whenever ...

As scientific and engineering domains attempt to effectively analyze the deluge of data from sensors and instruments, machine learning is becoming a key data mining tool to build prediction models. Regression tree is a popular learning model that ...

In this paper we introduce a new approach to automatic attribute and granularity selection for building optimum regression trees. The method is based on the minimum description length principle (MDL) and aspects of granular computing. The approach is ...

Protein threading is one of the most successful protein structure prediction methods. Most protein threading methods use a scoring function linearly combining sequence and structure features to measure the quality of a sequence-template alignment so ...