Seleksi Fitur untuk Data Churn for Bank Customers Menggunakan Analisis Korelasi Pearson
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M. E. Morocho-Cayamcela, H. Lee, dan W. Lim, “Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions,” IEEE Access, vol. 7, hlm. 137184–137206, 2019, doi: 10.1109/ACCESS.2019.2942390.
Z.-H. Zhou, “A brief introduction to weakly supervised learning,” National Science Review, vol. 5, no. 1, hlm. 44–53, Agu 2017, doi: 10.1093/nsr/nwx106.
S. N. Shukla dan B. M. Marlin, “Interpolation-Prediction Networks for Irregularly Sampled Time Series,” 2019.
N. Papernot dan P. D. McDaniel, “Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning,” CoRR, vol. abs/1803.04765, 2018, [Daring]. Tersedia pada: http://arxiv.org/abs/1803.04765
H. Saadatfar, S. Khosravi, J. H. Joloudari, A. Mosavi, dan S. Shamshirband, “A New K-Nearest Neighbors Classifier for Big Data Based on Efficient Data Pruning,” Mathematics, vol. 8, no. 2, 2020, doi: 10.3390/math8020286.
R. Ahuja, A. Solanki, dan A. Nayyar, “Movie Recommender System Using K-Means Clustering AND K-Nearest Neighbor,” dalam 2019 9th International Conference on Cloud Computing, Data Science Engineering (Confluence), 2019, hlm. 263–268. doi: 10.1109/CONFLUENCE.2019.8776969.
Kaggle, “Getting Started on Kaggle | Data Scxience Resources,” 2022. https://www.kaggle.com/docs
Y. Liu, Y. Mu, K. Chen, Y. Li, dan J. Guo, “Daily activity feature selection in smart homes based on pearson correlation coefficient,” Neural Processing Letters, vol. 51, no. 2, hlm. 1771–1787, 2020.
D. Risqiwati, A. D. Wibawa, E. S. Pane, W. R. Islamiyah, A. E. Tyas, dan M. H. Purnomo, “Feature Selection for EEG-Based Fatigue Analysis Using Pearson Correlation,” dalam 2020 International Seminar on Intelligent Technology and Its Applications (ISITIA), 2020, hlm. 164–169. doi: 10.1109/ISITIA49792.2020.9163760.
Y. Sugianela dan T. Ahmad, “Pearson Correlation Attribute Evaluation-based Feature Selection for Intrusion Detection System,” dalam 2020 International Conference on Smart Technology and Applications (ICoSTA), 2020, hlm. 1–5. doi: 10.1109/ICoSTA48221.2020.1570613717.
Kaggle, “Churn for Bank Customers.” 2020. [Daring]. Tersedia pada: https://www.kaggle.com/mathchi/churn-for-bank-customers
DOI: https://doi.org/10.31284/p.snestik.2022.2927
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