Related papers: Implementation of the Random Forest Method for the…
This paper is devoted to the problem of detection of forest and non-forest areas on Earth images. We propose two statistical methods to tackle this problem: one based on multiple hypothesis testing with parametric distribution families,…
The spanning tree heuristic is a commonly adopted procedure in network inference and estimation. It allows one to generalize an inference method developed for trees, which is usually based on a statistically rigorous approach, to a…
Atmospheric Cerenkov telescopes are used to detect electromagnetic showers from primary gamma rays of energy ~300 GeV - ~10 TeV and to discriminate these from cascades due to hadrons using the Cerenkov images. The geomagnetic field affects…
The MAGIC telescope is an imaging atmospheric Cherenkov telescope, designed to observe very high energy gamma-rays while achieving a low energy threshold. One of the key science goals is fast follow-up of the enigmatic and short lived…
Canonical distances such as Euclidean distance often fail to capture the appropriate relationships between items, subsequently leading to subpar inference and prediction. Many algorithms have been proposed for automated learning of suitable…
Random forests are popular methods for regression and classification analysis, and many different variants have been proposed in recent years. One interesting example is the Mondrian random forest, in which the underlying constituent trees…
Over the last three decades, the ground-based technique of imaging atmospheric Cherenkov telescopes has established itself as a powerful scientific discipline. About 250 very high gamma-ray sources of both galactic and extragalactic origin…
As a flexible nonparametric learning tool, the random forests algorithm has been widely applied to various real applications with appealing empirical performance, even in the presence of high-dimensional feature space. Unveiling the…
In this article, we strengthen the proof methods of some previously weakly consistent variants of random forests into strongly consistent proof methods, and improve the data utilization of these variants, in order to obtain better…
In this paper we describe the different software and hardware elements of a mini-telescope for the detection of cosmic rays and gamma-rays using the Cherenkov light emitted by their induced particle showers in the atmosphere. We estimate…
In this work, we present a new, high performance algorithm for background rejection in imaging atmospheric Cherenkov telescopes. We build on the already popular machine-learning techniques used in gamma-ray astronomy by the application of…
We describe the use of an unsupervised Random Forest for similarity learning and improved unsupervised anomaly detection. By training a Random Forest to discriminate between real data and synthetic data sampled from a uniform distribution…
Context. We are operating an elastic LIDAR for the monitoring of atmospheric conditions during regular observations of the MAGIC Telescopes. Aims. We present and evaluate methods to convert aerosol extinction profiles, obtained with the…
Ground based Cherenkov telescope systems measure astrophysical gamma-ray emission against a background of cosmic-ray induced air showers. The subtraction of this background is a major challenge for the extraction of spectra and morphology…
We propose a random forest (RF) machine learning approach to determine the accreted stellar mass fractions ($f_\mathrm{acc}$) of central galaxies, based on various dark matter halo and galaxy features. The RF is trained and tested using…
We propose a novel method designed for large-scale regression problems, namely the two-stage best-scored random forest (TBRF). "Best-scored" means to select one regression tree with the best empirical performance out of a certain number of…
In February 2007 the MAGIC Air Cherenkov Telescope for gamma-ray astronomy was fully upgraded with an ultra fast 2 GSamples/s digitization system. Since the Cherenkov light flashes are very short, a fast readout can minimize the influence…
Random Forest has become one of the most popular tools for feature selection. Its ability to deal with high-dimensional data makes this algorithm especially useful for studies in neuroimaging and bioinformatics. Despite its popularity and…
The existing methods for detection of the cloud scenes are applied at relatively small spectral range within shortwave upwelling radiative wavelength flux. We have reported a new method for detection of the cloud scenes based on the…
The hydrometallurgical method of zinc production involves leaching zinc from ore and then separating the solid residue from the liquid solution by pressure filtration. This separation process is very important since the solid residue…