Students Performance Data Mining by Shaukat Kamran (4 results)

Paperback. Condition: Brand New. 56 pages. 8.66x5.91x0.13 inches. In Stock.

Taschenbuch. Condition: Neu. Student's Performance: A Data Mining Perspective | Kamran Shaukat (u. a.) | Taschenbuch | 56 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202024013 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data Mining is an emerging field used in educational purposes to improve the perceptive and learning method of students. It focuses on recognizing, extracting and calculating data associated to the learning method and improving student's performance. Mining in a learning field is known as educational information mining which is fretful with exploring latest techniques to find out knowledge from educational fields. The purpose of our study is to evaluate the performance of students by taking different attributes like academic achievements (CGPA), gender, class test grade, environment of class, Fund/Scholarships/Private etc. In our research we will use classification and clustering techniques to analyze student performance. The techniques used in our work are decision tree, Bayesian classification-mean algorithms, neural networks, naïve's bayes, Web based system and nearest neighbor methods.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data Mining is an emerging field used in educational purposes to improve the perceptive and learning method of students. It focuses on recognizing, extracting and calculating data associated to the learning method and improving student's performance. Mining in a learning field is known as educational information mining which is fretful with exploring latest techniques to find out knowledge from educational fields. The purpose of our study is to evaluate the performance of students by taking different attributes like academic achievements (CGPA), gender, class test grade, environment of class, Fund/Scholarships/Private etc. In our research we will use classification and clustering techniques to analyze student performance. The techniques used in our work are decision tree, Bayesian classification-mean algorithms, neural networks, naïve's bayes, Web based system and nearest neighbor methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.…