Finding habitable exo planets using boosting algorithm
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2018.
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| Lingua: | English |
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Brac University
2020
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| Accesso online: | http://hdl.handle.net/10361/13653 |
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10361-136532022-01-26T10:10:33Z Finding habitable exo planets using boosting algorithm Rahman, Md. Mashfiq Afrin, Naba Majumdar, Mahbub Alam Department of Computer Science and Engineering, Brac University Boosting algorithm This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 39-41). The first moment man extended their boundaries outside of our Earth, from that moment they were looking for another habitable planet, where they may live in future. Including NASA, many international space organization already sent a number of satellite on this mission. These mission have discovered thousands of new planetary candidates, many of which have been confirmed through follow up observations. A primary goal of the mission is to determine the occurrence rate of terrestrial-size planets within the Habitable Zone (HZ) of their host stars. Though many approaches have been taken to confirm their habitability, we tried a new approach by using boosting algorithms. We use the NASAs Extra Solar planets dataset of 3,577 planets and use their various characteristics like their Mass, Radius, Orbital Eccentricity, Temperature, Metallicity to determine the best set of alternatives of Earth. We classified the dataset based on these variables and used Extreme Gradient Boosting to compare the accuracy to find out our desirable results. We used different classifier to ensure the best accuracy. So we used Ada Boosting Classifier, KNeighbor’s Nearest Classifier (KNN), Gradient Boosting Classifier, Decision Tree Classifier and Random Forest Classifier into our dataset. Md. Mashfiq Rahman Naba Afrin B. Computer Science 2020-01-21T07:39:27Z 2020-01-21T07:39:27Z 2018 2018-12 Thesis ID 12301006 ID 14301090 http://hdl.handle.net/10361/13653 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 41 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Boosting algorithm |
| spellingShingle |
Boosting algorithm Rahman, Md. Mashfiq Afrin, Naba Finding habitable exo planets using boosting algorithm |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2018. |
| author2 |
Majumdar, Mahbub Alam |
| author_facet |
Majumdar, Mahbub Alam Rahman, Md. Mashfiq Afrin, Naba |
| format |
Thesis |
| author |
Rahman, Md. Mashfiq Afrin, Naba |
| author_sort |
Rahman, Md. Mashfiq |
| title |
Finding habitable exo planets using boosting algorithm |
| title_short |
Finding habitable exo planets using boosting algorithm |
| title_full |
Finding habitable exo planets using boosting algorithm |
| title_fullStr |
Finding habitable exo planets using boosting algorithm |
| title_full_unstemmed |
Finding habitable exo planets using boosting algorithm |
| title_sort |
finding habitable exo planets using boosting algorithm |
| publisher |
Brac University |
| publishDate |
2020 |
| url |
http://hdl.handle.net/10361/13653 |
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AT rahmanmdmashfiq findinghabitableexoplanetsusingboostingalgorithm AT afrinnaba findinghabitableexoplanetsusingboostingalgorithm |
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