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Complexity measure of extreme events.
Chaos
December 2024
Division of Dynamics, Technical University of Lodz, Stefanovskiego 1/15, 90-924 Lodz, Poland.
Complexity is an important metric for appropriate characterization of different classes of irregular signals, observed in the laboratory or in nature. The literature is already rich in the description of such measures using a variety of entropy and disequilibrium measures, separately or in combination. Chaotic signal was given prime importance in such studies while no such measure was proposed so far, how complex were the extreme events when compared to non-extreme chaos.
View Article and Find Full Text PDFExtremely Randomized Machine Learning Methods for Compound Activity Prediction.
Molecules
November 2015
Institute of Pharmacology, Polish Academy of Sciences, Smetna 12, 31-343 Krakow, Poland.
Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called 'extremely randomized methods'-Extreme Entropy Machine and Extremely Randomized Trees-for their ability to properly identify compounds that have activity towards particular protein targets.
View Article and Find Full Text PDFEntropy of nonextreme charged rotating black holes in string theory.
Phys Rev D Part Fields
August 1996
Erratum: Action and entropy of extreme and nonextreme black holes.
Phys Rev D Part Fields
November 1995
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