Articles liés à Data mining using neural network
Synopsis
At the present time, the amount of data stored in educational database is increasing rapidly. These databases contain hidden information for improvement of student’s performance. Decision tree is the most useful classification algorithm in educational data mining because of its ease of execution and easier to understand compared to other algorithms. We can get more accurate and valuable results with the help of decision tree algorithm which can be useful for instructors to improve the student learning outcomes. The ID3, C4.5 and CART decision tree algorithms has been applied on the data of students to predict their performance. But all these 3 algorithms are used only for small database. For large database, we are using a new algorithm i.e. SPRINT which removes all the memory restriction and accuracy problem comes in other algorithms. It is fast and scalable than others because it can be implemented in both serial and parallel fashion for good data placement and load balancing. In this work, SPRINT decision tree algorithm is used to solve the problem of classification in education system.
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À propos de l'auteur
Assistant Professor in the Department of Computer Science at DSMNRU. He has been associated with the IT Industry, research and academics for the last twelve years. He has rich and diverse experience in academia and has been Visiting Professor at various Universities and Colleges.
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Data mining using neural network
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LAP LAMBERT Academic Publishing Jul 2017, 2017
ISBN 10 : 3330350415
ISBN 13 : 9783330350410
Neuf
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -At the present time, the amount of data stored in educational database is increasing rapidly. These databases contain hidden information for improvement of student's performance. Decision tree is the most useful classification algorithm in educational data mining because of its ease of execution and easier to understand compared to other algorithms. We can get more accurate and valuable results with the help of decision tree algorithm which can be useful for instructors to improve the student learning outcomes. The ID3, C4.5 and CART decision tree algorithms has been applied on the data of students to predict their performance. But all these 3 algorithms are used only for small database. For large database, we are using a new algorithm i.e. SPRINT which removes all the memory restriction and accuracy problem comes in other algorithms. It is fast and scalable than others because it can be implemented in both serial and parallel fashion for good data placement and load balancing. In this work, SPRINT decision tree algorithm is used to solve the problem of classification in education system. 60 pp. Englisch. N° de réf. du vendeur 9783330350410
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Data mining using neural network
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330350415
ISBN 13 : 9783330350410
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - At the present time, the amount of data stored in educational database is increasing rapidly. These databases contain hidden information for improvement of student's performance. Decision tree is the most useful classification algorithm in educational data mining because of its ease of execution and easier to understand compared to other algorithms. We can get more accurate and valuable results with the help of decision tree algorithm which can be useful for instructors to improve the student learning outcomes. The ID3, C4.5 and CART decision tree algorithms has been applied on the data of students to predict their performance. But all these 3 algorithms are used only for small database. For large database, we are using a new algorithm i.e. SPRINT which removes all the memory restriction and accuracy problem comes in other algorithms. It is fast and scalable than others because it can be implemented in both serial and parallel fashion for good data placement and load balancing. In this work, SPRINT decision tree algorithm is used to solve the problem of classification in education system. N° de réf. du vendeur 9783330350410
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Data mining using neural network
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330350415
ISBN 13 : 9783330350410
Neuf
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Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Katiyar DeveshAssistant Professor in the Department of Computer Science at DSMNRU. He has been associated with the IT Industry, research and academics for the last twelve years. He has rich and diverse experience in academia and has . N° de réf. du vendeur 158799535
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Data mining using neural network
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330350415
ISBN 13 : 9783330350410
Neuf
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Paperback. Etat : Brand New. 60 pages. 8.66x5.91x0.14 inches. In Stock. N° de réf. du vendeur __3330350415
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Data mining using neural network
Edité par
LAP LAMBERT Academic Publishing Jul 2017, 2017
ISBN 10 : 3330350415
ISBN 13 : 9783330350410
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -At the present time, the amount of data stored in educational database is increasing rapidly. These databases contain hidden information for improvement of student's performance. Decision tree is the most useful classification algorithm in educational data mining because of its ease of execution and easier to understand compared to other algorithms. We can get more accurate and valuable results with the help of decision tree algorithm which can be useful for instructors to improve the student learning outcomes. The ID3, C4.5 and CART decision tree algorithms has been applied on the data of students to predict their performance. But all these 3 algorithms are used only for small database. For large database, we are using a new algorithm i.e. SPRINT which removes all the memory restriction and accuracy problem comes in other algorithms. It is fast and scalable than others because it can be implemented in both serial and parallel fashion for good data placement and load balancing. In this work, SPRINT decision tree algorithm is used to solve the problem of classification in education system.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. N° de réf. du vendeur 9783330350410
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