Open Access
Issue |
ITM Web Conf.
Volume 58, 2024
The 6th IndoMS International Conference on Mathematics and Applications (The 6th IICMA 2023)
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|
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Article Number | 04006 | |
Number of page(s) | 14 | |
Section | Statistics | |
DOI | https://doi.org/10.1051/itmconf/20245804006 | |
Published online | 09 January 2024 |
- Bain, L. J., & Engelgardt, M, Introduction to Probability and Mathematical Statistics, Second Edition (Duxbury, California, 1992) [Google Scholar]
- Dianasari, T. Evaluasi Kinerja Backpropagation, Extreme Gradient Boosting, Feedforward Network Pada Klasifikasi Klien Berlangganan Deposito Berjangka (Universitas Gadjah Mada, Yogyakarta, 2019) [Google Scholar]
- Guo, L. (n.d.). Applying Data Mining Techniques in Property/Casualty Insurance. Florida: University of Central Florida. [Google Scholar]
- Han, J., Kamber, M., & Pei, J. Data Mining: Concepts and Techniques. Elsevier Inc, 3rd Edition (2012) [Google Scholar]
- Harris, M, Multiclass Classification with XGBoost in R (2017) [Google Scholar]
- Hidayat, A, Penjelasan Lengkap Tentang Analisis Cluster (2014) [Google Scholar]
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (20113). An Introduction to StatisticaL Learning with Application in R. New York: Springer. [Google Scholar]
- Jasmi, R. Simple Tutorial on SVM and Parameter Tuning in Python and R (2017) [Google Scholar]
- Kassambara, A. CLARA in R: Clustering Large Applications (2018) [Google Scholar]
- Kassambara, A. Determining The Optimal Number Of Clusters: 3 Must Know Methods (2018) [Google Scholar]
- Kryńska, K. Using K-means and PAM clustering for Customer Segmentation (2018) [Google Scholar]
- Li, C. (n.d.). A Gentle Introduction to Gradient Boosting. [Google Scholar]
- Luo, Y., Pang, S., & Qiu, S. (2003). Fuzzy Cluster in Credit Scoring. Proceedings of the Second International Conference on Machine Learning and Cybernetics. Retrieved May 19, 2020. [Google Scholar]
- Magdalena, R, IFRS 17 Decoded (2019) [Google Scholar]
- Manish, S. (n.d.). Beginners Tutorial on XGBoost and Parameter Tuning in R. [Google Scholar]
- Muskitta, C. R., & Safitri, K. A. JABT, 2 (2019) [Google Scholar]
- Muslim, A. B. Analisis Klaster Menggunakan Metode Clara Pada Data Yang Mengandung Pencilan. (Universitas Gadjah Mada, Yogyakarta, 2018) [Google Scholar]
- Octavian, A. P., Wilandari, Y., & Ispriyanti, D, 811-820 (2014) [Google Scholar]
- Pradeep, S, Machine Learning Case study : SVM (2015) [Google Scholar]
- Rdusseeun, L. K. P. J., & Kaufman, P. Clustering By Means of Medoids. Proceedings of the Statistical Data Analysis Based on the L1 Norm Conference (1987) [Google Scholar]
- Muskitta, C. R., & Safitri, K. A, JABT, 2 (2019) [Google Scholar]
- Zhu, J., Rosset, S., Hui, Z., & Hastie, T. Multi-Class AdaBoost. (University of Michigan, Michigan, 2006) [Google Scholar]
- Zulhanif, Algoritma AdaBoost Dalam Pengklasifikasian. (Pendidikan Matematika UMS, Surakarta, 2015) [Google Scholar]
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