A survey on machine learning for recurring concept drifting data streams

The problem of concept drift has gained a lot of attention in recent years. This aspect is key in many domains exhibiting non-stationary as well as cyclic patterns and structural breaks affecting their generative processes. In this survey, we review the relevant literature to deal with regime changes in the behaviour of continuous data streams. The study starts with a general introduction to the field of data stream learning, describing recent works on passive or active mechanisms to adapt or detect concept drifts, frequent challenges in this area, and related performance metrics. Then, different supervised and non-supervised approaches such as online ensembles, meta-learning and model-based clustering that can be used to deal with seasonalities in a data stream are covered. The aim is to point out new research trends and give future research directions on the usage of machine learning techniques for data streams which can help in the event of shifts and recurrences in continuous learning scenarios in near real-time

Machine Learning for Financial Prediction Under Regime Change Using Technical Analysis: A Systematic Review

Recent crises, recessions and bubbles have stressed the non-stationary nature and the presence of drastic structural changes in the financial domain. The most recent literature suggests the use of conventional machine learning and statistical approaches in this context. Unfortunately, several of these techniques are unable or slow to adapt to changes in the price-generation process. This study aims to survey the relevant literature on Machine Learning for financial prediction under regime change employing a systematic approach. It reviews key papers with a special emphasis on technical analysis. The study discusses the growing number of contributions that are bridging the gap between two separate communities, one focused on data stream learning and the other on economic research. However, it also makes apparent that we are still in an early stage. The range of machine learning algorithms that have been tested in this domain is very wide, but the results of the study do not suggest that currently there is a specific technique that is clearly dominant

Incremental Market Behavior Classification in Presence of Recurring Concepts

In recent years, the problem of concept drift has gained importance in the financial domain. The succession of manias, panics and crashes have stressed the non-stationary nature and the likelihood of drastic structural or concept changes in the markets. Traditional systems are unable or slow to adapt to these changes. Ensemble-based systems are widely known for their good results predicting both cyclic and non-stationary data such as stock prices. In this work, we propose RCARF (Recurring Concepts Adaptive Random Forests), an ensemble tree-based online classifier that handles recurring concepts explicitly. The algorithm extends the capabilities of a version of Random Forest for evolving data streams, adding on top a mechanism to store and handle a shared collection of inactive trees, called concept history, which holds memories of the way market operators reacted in similar circumstances. This works in conjunction with a decision strategy that reacts to drift by replacing active trees with the best available alternative: either a previously stored tree from the concept history or a newly trained background tree. Both mechanisms are designed to provide fast reaction times and are thus applicable to high-frequency data. The experimental validation of the algorithm is based on the prediction of price movement directions one second ahead in the SPDR (Standard & Poor's Depositary Receipts) S&P 500 Exchange-Traded Fund. RCARF is benchmarked against other popular methods from the incremental online machine learning literature and is able to achieve competitive results.This research was funded by the Spanish Ministry of Economy and Competitiveness under grant number ENE2014-56126-C2-2-R

Mechanistic versatility at Ir(PSiP) pincer catalysts: triflate proton shuttling from 2-Butyne to Diene and [3]Dendralene motifs

The five-coordinate hydrido complex [IrH(OTf)(PSiP)] (1) catalytically transforms 2-butyne into a mixture of its isomer 1,3-butadiene, and [3]dendralene and linear hexatriene dimerization products: (E)-4-methyl-3-methylene-1,4-hexadiene and (3Z)-3,4-dimethyl-1,3,5-hexatriene, respectively. Under the conditions of the catalytic reaction, benzene, and 363 K, the hexatriene further undergoes thermal electrocyclization into 2,3-dimethyl-1,3-cyclohexadiene. The reactions between 1 and the alkyne substrate allow isolation or nuclear magnetic resonance (NMR) observation of catalyst resting states and possible reaction intermediates, including complexes with the former PSiP pincer ligands disassembled into PSi and PC chelates, and species coordinating allyl or carbene fragments en route to products. The density functional theory (DFT) calculations guided by these experimental observations disclose competing mechanisms for C–H bond elaboration that move H atoms either classically, as hydrides, or as protons transported by the triflate. This latter role of triflate, previously recognized only for more basic anions such as carboxylates, is discussed to result from combining the unfavorable charge separation in the nonpolar solvent and the low electronic demand from the metal to the anion at coordination positions trans to silicon. Triflate deprotonation of methyl groups is key to release highly coordinating diene products from stable allyl intermediates, thus enabling catalytic cycling

CNO behaviour in planet-harbouring stars. II. Carbon abundances in stars with and without planets using the CH band

Context. Carbon, oxygen and nitrogen (CNO) are key elements in stellar formation and evolution, and their abundances should also have a significant impact on planetary formation and evolution. Aims. We present a detailed spectroscopic analysis of 1110 solar-type stars, 143 of which are known to have planetary companions. We have determined the carbon abundances of these stars and investigate a possible connection between C and the presence of planetary companions. Methods. We used the HARPS spectrograph to obtain high-resolution optical spectra of our targets. Spectral synthesis of the CH band at 4300\AA was performed with the spectral synthesis codes MOOG and FITTING. Results. We have studied carbon in several reliable spectral windows and have obtained abundances and distributions that show that planet host stars are carbon rich when compared to single stars, a signature caused by the known metal-rich nature of stars with planets. We find no different behaviour when separating the stars by the mass of the planetary companion. Conclusions. We conclude that reliable carbon abundances can be derived for solar-type stars from the CH band at 4300\AA. We confirm two different slope trends for [C/Fe] with [Fe/H] because the behaviour is opposite for stars above and below solar values. We observe a flat distribution of the [C/Fe] ratio for all planetary masses, a finding that apparently excludes any clear connection between the [C/Fe] abundance ratio and planetary mass.Comment: 10 pages, 10 figures. Accepted to A&

SWEET-Cat update and FASMA. A new minimization procedure for stellar parameters using high-quality spectra

Context : Thanks to the importance that the star-planet relation has to our understanding of the planet formation process, the precise determination of stellar parameters for the ever increasing number of discovered extrasolar planets is of great relevance. Furthermore, precise stellar parameters are needed to fully characterize the planet properties. It is thus important to continue the efforts to determine, in the most uniform way possible, the parameters for stars with planets as new discoveries are announced. Aims : In this paper we present new precise atmospheric parameters for a sample of 50 stars with planets. The results are presented in the catalogue: SWEET-Cat. Methods : Stellar atmospheric parameters and masses for the 50 stars were derived assuming local thermodynamic equilibrium (LTE) and using high-resolution and high signal-to-noise spectra. The methodology used is based on the measurement of equivalent widths with ARES2 for a list of iron lines. The line abundances were derived using MOOG. We then used the curve of growth analysis to determine the parameters. We implemented a new minimization procedure which significantly improves the computational time. Results : The stellar parameters for the 50 stars are presented and compared with previously determined literature values. For SWEET-Cat, we compile values for the effective temperature, surface gravity,metallicity, and stellar mass for almost all the planet host stars listed in the Extrasolar Planets Encyclopedia. This data will be updated on a continuous basis. The data can be used for statistical studies of the star-planet correlation, and for the derivation of consistent properties for known planets.PostprintPeer reviewe

Spring-neap tidal and circadian variability in the distribution of two groups of Pseudo-nitzschia species in an upwelling influenced estuary

High-resolution physical and biological measurements were carried out in the Ría de Pontevedra (NW Spain) in late spring during the ‘HABIT Pontevedra 2007’ survey, which utilized high vertical resolution instruments. Cell maxima of P. delicatissima (6 x 105 cells L-1) and P. seriata (2 x 106 cells L-1) groups were observed during the first half of the cruise during downwelling and a significant decrease in cell numbers occurred during subsequent upwelling conditions. The effect of tidal (both semidiurnal and spring-neap) and event driven (upwelling-downwelling cycle) variability were evident. The observed sequence of events suggests that Pseudo-nitzschia populations were advected from the shelf. The circadian variability was regulated by tidal forcing and Pseudo-nitzschia spp. maxima were observed at low tide. From results presented here we conclude that the magnitude of spring-neap tidal and circadian variability has to be considered when designing and implementing harmful algal bloom monitoring programmesEn prens

The 1989 and 2015 outbursts of V404 Cygni: a global study of wind-related optical features

The black hole transient V404 Cygni exhibited a bright outburst in June 2015 that was intensively followed over a wide range of wavelengths. Our team obtained high time resolution optical spectroscopy (~90 s), which included a detailed coverage of the most active phase of the event. We present a database consisting of 651 optical spectra obtained during this event, that we combine with 58 spectra gathered during the fainter December 2015 sequel outburst, as well as with 57 spectra from the 1989 event. We previously reported the discovery of wind-related features (P-Cygni and broad-wing line profiles) during both 2015 outbursts. Here, we build diagnostic diagrams that enable us to study the evolution of typical emission line parameters, such as line fluxes and equivalent widths, and develop a technique to systematically detect outflow signatures. We find that these are present throughout the outburst, even at very low optical fluxes, and that both types of outflow features are observed simultaneously in some spectra, confirming the idea of a common origin. We also show that the nebular phases depict loop patterns in many diagnostic diagrams, while P-Cygni profiles are highly variable on time-scales of minutes. The comparison between the three outbursts reveals that the spectra obtained during June and December 2015 share many similarities, while those from 1989 exhibit narrower emission lines and lower wind terminal velocities. The diagnostic diagrams presented in this work have been produced using standard measurement techniques and thus may be applied to other active low-mass X-ray binaries.Comment: Accepted for publication in MNRAS. 23 pages paper, plus a 9 pages appendix with extra tables and figures. 18 figures are included in the paper and 8 in the appendi

The GW Vir instability strip in the light of new observations of PG 1159 stars. Discovery of pulsations in the central star of Abell 72 and variability of RX J0122.9-7521

We present the results of new time series photometric observations of 29 pre-white dwarf stars of PG 1159 spectral type, carried out in the years 2014-2022. For the majority of stars, a median noise level in Fourier amplitude spectra of 0.5-1.0 mmag was achieved. This allowed the detection of pulsations in the central star of planetary nebula Abell 72, consistent with g-modes excited in GW Vir stars, and variability in RX J0122.9-7521 that could be due to pulsations, binarity or rotation. For the remaining stars from the sample that were not observed to vary, we placed upper limits for variability. After combination with literature data, our results place the fraction of pulsating PG 1159 stars within the GW Vir instability strip at 36%. An updated list of all known PG 1159 stars is provided, containing astrometric measurements from the recent Gaia DR3 data, as well as information on physical parameters, variability, and nitrogen content. Those data are used to calculate luminosities for all PG 1159 stars to place the whole sample on the theoretical Hertzsprung-Russell diagram for the first time in that way. The pulsating stars are discussed as a group, and arguments are given that the traditional separation of GW Vir pulsators in "DOV" and "PNNV" stars is misleading and should not be used.Comment: Accepted for publication in ApJ