As an emerging subject with strong comprehensiveness, machine learning has made varying degrees of progress in various fields. In the field of astronomy, it has also been generally used, and there have been quantities of research using machine learning for data processing and model prediction. The paper has used three algorithms (Decision Tree, Random Forest and Support Vector Machine) to build prediction models to classify stars, galaxies, and quasars in the universe and make a comparison among three models. The results of the test have shown that the prediction accuracy of the Random Forest model reaches roughly 98 percent with a great computing efficiency, which performs the best
Context. Future astrophysical surveys such as J-PAS will produce very large datasets, the so-called ...
An emerging issue in the field of astronomy is the integration, management and utilization of databa...
A new Gaia data release, EDR3, has been available since the end of last year containing a complete c...
As an emerging subject with strong comprehensiveness, machine learning has made varying degrees of p...
The objective of this study was to create a predictive model to classify stars, galaxies, and quasar...
We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to t...
Lightyears beyond the Planet Earth there exist plenty of unknown and unexplored stars and Galaxies t...
This is version 1, you should use the updated version 2 that was accepted for publication: 10.5281/z...
Gaia space astrometry mission will scan about one billion stars an average of 70 times each over fiv...
This is the same as the published data available under 10.5281/zenodo.3768398, but in the format of ...
In the paper Sloan Digital Sky Survey DR14 dataset was investigated. It contains statistical informa...
The application of machine learning (ML) techniques to simulated cosmological data aids in the devel...
With the increasing amounts of astronomical data being gathered, it is becoming more crucial for mac...
In this work, I investigate the possibility of finding a data-driven solution to the problem of auto...
We apply machine learning techniques in an attempt to predict and classify stellar properties from n...
Context. Future astrophysical surveys such as J-PAS will produce very large datasets, the so-called ...
An emerging issue in the field of astronomy is the integration, management and utilization of databa...
A new Gaia data release, EDR3, has been available since the end of last year containing a complete c...
As an emerging subject with strong comprehensiveness, machine learning has made varying degrees of p...
The objective of this study was to create a predictive model to classify stars, galaxies, and quasar...
We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to t...
Lightyears beyond the Planet Earth there exist plenty of unknown and unexplored stars and Galaxies t...
This is version 1, you should use the updated version 2 that was accepted for publication: 10.5281/z...
Gaia space astrometry mission will scan about one billion stars an average of 70 times each over fiv...
This is the same as the published data available under 10.5281/zenodo.3768398, but in the format of ...
In the paper Sloan Digital Sky Survey DR14 dataset was investigated. It contains statistical informa...
The application of machine learning (ML) techniques to simulated cosmological data aids in the devel...
With the increasing amounts of astronomical data being gathered, it is becoming more crucial for mac...
In this work, I investigate the possibility of finding a data-driven solution to the problem of auto...
We apply machine learning techniques in an attempt to predict and classify stellar properties from n...
Context. Future astrophysical surveys such as J-PAS will produce very large datasets, the so-called ...
An emerging issue in the field of astronomy is the integration, management and utilization of databa...
A new Gaia data release, EDR3, has been available since the end of last year containing a complete c...