{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T11:14:47Z","timestamp":1781781287273,"version":"3.54.5"},"reference-count":53,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T00:00:00Z","timestamp":1686182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Over time, human beings have built increasingly large astronomical observatories to increase the number of discoveries related to celestial objects. However, the amount of collected elements far exceeds the human capacity to analyze findings without help. For this reason, researchers must now turn to machine learning to analyze such data, identifying and classifying transient objects or events within extensive observations of the firmament. Algorithms from the family of random forests (an ensemble of decision trees) have become a powerful tool that can be used to classify astronomical events and objects. This work aims to illustrate the versatility of machine learning algorithms, such as decision trees, to facilitate the identification and classification of celestial bodies by manipulating hyperparameters and studying the attributes of celestial body datasets. By applying a random forest algorithm to a well-known dataset that includes three types of celestial bodies, its effectiveness was compared against some supervised classifiers of the most important approaches (Bayes, nearest neighbors, support vector machines, and neural networks). The results show that random forests are a good alternative for data analysis and classification in astronomical observations.<\/jats:p>","DOI":"10.3390\/a16060293","type":"journal-article","created":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T03:29:48Z","timestamp":1686194988000},"page":"293","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Random forest Algorithm for the Classification of Spectral Data of Astronomical Objects"],"prefix":"10.3390","volume":"16","author":[{"given":"Jos\u00e9-Luis","family":"Solorio-Ram\u00edrez","sequence":"first","affiliation":[{"name":"Centro de Investigaci\u00f3n en Computaci\u00f3n del Instituto Polit\u00e9cnico Nacional, Juan de Dios B\u00e1tiz s\/n, GAM, CDMX 07700, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ra\u00fal","family":"Jim\u00e9nez-Cruz","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n en Computaci\u00f3n del Instituto Polit\u00e9cnico Nacional, Juan de Dios B\u00e1tiz s\/n, GAM, CDMX 07700, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9889-3924","authenticated-orcid":false,"given":"Yenny","family":"Villuendas-Rey","sequence":"additional","affiliation":[{"name":"Instituto Tecnol\u00f3gico y de Estudios Superiores de Monterrey Campus Ciudad de M\u00e9xico, Prolongaci\u00f3n Canal de Miramontes, Coapa, San Bartolo el Chico, CDMX 14380, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6250-4728","authenticated-orcid":false,"given":"Cornelio","family":"Y\u00e1\u00f1ez-M\u00e1rquez","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n en Computaci\u00f3n del Instituto Polit\u00e9cnico Nacional, Juan de Dios B\u00e1tiz s\/n, GAM, CDMX 07700, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,8]]},"reference":[{"key":"ref_1","first-page":"115","article-title":"The message of some ancient astronomical symbols from the oldest neolithic Vin\u010ca civilization (Mostonga, T\u0103rt\u0103ria, Turda\u015f and Par\u0163a)","volume":"31","year":"2021","journal-title":"Rom. 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