EISCAT VHF radar data are used for observing, monitoring, and understanding Earth’s upper atmosphere. This paper presents an approach to segment Polar Mesospheric Summer Echoes (PMSE) from datasets obtained data. The consist of 30 observations days, corresponding 56,250 samples. We manually labeled the into three different categories: PMSE, Ionospheric background, Background noise. For segmenta...

In an era of strong customer relationship management (CRM) emphasis, firms strive to build valuable relationships with their existing customer base. In this study we attempt to better understand three important measures of customer outcome: next buy, partial defection and customers’ profitability evolution. By means of random forests techniques we investigate a broad set of explanatory variable...

In this paper, we propose an improved random forest algorithm which allocates weights to decision trees in the forest during tree aggregation for prediction and their weights are easily calculated based on out-of-bag errors in training. Experiments results show that our proposed algorithm beats the original random forest and other popular classification algorithms such as SVM, KNN and C4.5 in t...

Minimal depth is a dimensionless order statistic that measures the predictiveness of a variable in a survival tree. It can be used to select variables in high-dimensional problems using Random Survival Forests (RSF), a new extension of Breiman’s Random Forests (RF) to survival settings. We review this methodology and demonstrate its use in high-dimensional survival problems using a public domai...

Despite widespread interest and practical use, the theoretical properties of random forests are still not well understood. In this paper we contribute to this understanding in two ways. We present a new theoretically tractable variant of random regression forests and prove that our algorithm is consistent. We also provide an empirical evaluation, comparing our algorithm and other theoretically ...

Various random combinatorial objects, such as mappings, trees, forests, and subsets of a finite set, are constructed with probability distributions related to the binomial and multinomial expansions due to Abel, Cayley and Hurwitz. Relations between these combinatorial objects, such as Joyal’s bijection between mappings and marked rooted trees, have interesting probabilistic interpretations, an...

This paper presents an approach integrating complex aggregate features into a relational random forest learner to address relational data mining tasks. CARAF, for Complex Aggregates within RAndom Forests, has two goals. Firstly, it aims at avoiding exhaustive exploration of the large feature space induced by the use of complex aggregates. Its second purpose is to reduce the overfitting introduc...

The impact of random choices is important to many ensemble classifiers algorithms, and the Random Forests is particularly sensible to pseudo-random number generation decisions. This paper proposes an extension to the classical Random Forests method that aims to reduce its sensibility to randomness. The benefits brought by such extension are illustrated by a large number of experiments over 32 d...

The extraction and exploitation of existing knowledge assets for supporting decision making and increasing the effectiveness of various internal and external interventions is of critical importance for the success of modern organizations. The use of advanced Operational Research-based quantitative methods in combination with high capabilities information systems can be very useful for this purp...