Prediksi Kelulusan Siswa Menggunakan Logistic Regression dan Optimasi Adam
(1) Universitas Muhammadiyah Semarang
(2) 
(*) Corresponding Author
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J. R. Quinlan, "Induction of Decision Trees," Machine Learning, vol. 1, no. 1, pp. 81–106, 1986. doi: 10.1023/A:1022643204877.
S. Hussain, D. Zhu, N. Zhang, dan L. Abidi, "Student Academic Performance Prediction using Logistic Regression, K-Means and Decision Tree," Proceedings of the 2020 IEEE Conference on Big Data, pp. 1809-1812, 2020. doi: 10.1109/BigData50022.2020.9378476.
R. Asif, A. Merceron, and S. A. Khan, "Predicting student academic performance using data from Learning Management Systems (LMS)," Educational Data Mining, vol. 1, no. 2, pp. 80–89, 2017.
S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge University Press, 2004.
D. P. Kingma and J. Ba, "Adam: A Method for Stochastic Optimization," arXiv preprint arXiv:1412.6980, 2014. [Online]. Available: https://arxiv.org/abs/1412.6980
I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. Cambridge, MA, USA: MIT Press, 2016.
S. Shalev-Shwartz and S. Ben-David, Understanding Machine Learning: From Theory to Algorithms. Cambridge, U.K.: Cambridge University Press, 2014.
I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. Cambridge, MA, USA: MIT Press, 2016.
J. Bergstra and Y. Bengio, "Random Search for Hyper-Parameter Optimization," Journal of Machine Learning Research, vol. 13, no. 1, pp. 281–305, 2012.
S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge University Press, 2004.
J. R. Quinlan, "Induction of Decision Trees," Machine Learning, vol. 1, no. 1, pp. 81–106, 1986. doi: 10.1023/A:1022643204877.
P. Domingos, "A Few Useful Things to Know About Machine Learning," Communications of the ACM, vol. 55, no. 10, pp. 78–87, 2012. doi: 10.1145/2347736.2347755.
F. Pedregosa et al., "Scikit-learn: Machine Learning in Python," Journal of Machine Learning Research, vol. 12, pp. 2825–2830, 2011.
D. Zhang and W. S. Lee, "Learning classifiers without negative examples: A reduction approach," in Proceedings of the 2005 SIAM International Conference on Data Mining, 2005, pp. 617–621. doi: 10.1137/1.9781611972757.69.
Y. LeCun, Y. Bengio, and G. Hinton, "Deep learning," Nature, vol. 521, no. 7553, pp. 436–444, 2015. doi: 10.1038/nature14539.
R. Kohavi and F. Provost, "Glossary of terms," Machine Learning, vol. 30, no. 2, pp. 271–274, 1998. doi: 10.1023/A:1017181826899.
R. Tibshirani, "Regression shrinkage and selection via the lasso: a retrospective," Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 73, no. 3, pp. 273–282, 2011. doi: 10.1111/j.1467-9868.2011.00771.x.
L. Bottou, "Large-scale machine learning with stochastic gradient descent," in Proceedings of COMPSTAT'2010, 2010, pp. 177–186. doi: 10.1007/978-3-7908-2604-3_16.
Y. Freund and R. E. Schapire, "A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting," Journal of Computer and System Sciences, vol. 55, no. 1, pp. 119–139, 1997. doi: 10.1006/jcss.1997.1504.
G. E. Hinton, S. Osindero, and Y.-W. Teh, "A fast learning algorithm for deep belief nets," Neural Computation, vol. 18, no. 7, pp. 1527–1554, 2006. doi: 10.1162/neco.2006.18.7.1527.
D. P. Bertsekas, "Incremental least-squares methods and the extended Kalman filter," SIAM Journal on Optimization, vol. 6, no. 3, pp. 807–822, 1996. doi: 10.1137/0806044.
C. Cortes and V. Vapnik, "Support-vector networks," Machine Learning, vol. 20, no. 3, pp. 273–297, 1995. doi: 10.1007/BF00994018.
S. Hochreiter and J. Schmidhuber, "Long Short-Term Memory," Neural Computation, vol. 9, no. 8, pp. 1735–1780, 1997. doi: 10.1162/neco.1997.9.8.1735.
G. Huang, Z. Liu, L. Van Der Maaten, and K. Q. Weinberger, "Densely Connected Convolutional Networks," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 4700–4708. doi: 10.1109/CVPR.2017.243.
M. Abadi et al., "TensorFlow: Large-scale machine learning on heterogeneous systems," Software available from tensorflow.org, 2015. [Online]. Available: https://www.tensorflow.org/
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DOI: https://doi.org/10.26714/jkti.v3i1.16189
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