Performance of Decision Tree C4.5 Algorithm in Student Academic Evaluation-Reference-Cited by-同舟云学术

Performance of Decision Tree C4.5 Algorithm in Student Academic Evaluation

Published:2018 Issue: Volume: Page:380-389
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Budiman Edy,Haviluddin ^ORCID,Dengan Nataniel,Kridalaksana Awang Harsa,Wati Masna,Purnawansyah

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-8276-4_36

Reference15 articles.

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2. Xu, B., et al.: Clustering educational digital library usage data: a comparison of latent class analysis and K-means algorithms. J. Educ. Data Min. 5(2), 38–68 (2013)

3. Mahboob, T., Irfan, S., Karamat, A.: A machine learning approach for student assessment in e-learning using Quinlan’s C4.5, Naïve Bayes and random forest algorithms. IEEE (2016)

4. Lakshmi, B.N., Indumathi, T.S., Ravi, N.: A study on C.5 decision tree classification algorithm for risk predictions during pregnancy. In: International Conference on Emerging Trends in Engineering, Science and Technology (ICETEST-2015), Procedia Technology (2016)

5. Haviluddin, et al.: Modelling of network traffic usage using self-organizing maps techniques. In: 2016 2nd International Conference on Science in Information Technology (ICSITech). IEEE (2016)

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