Accuracy evaluation of prediction using supervised learning techniques
Author:
Affiliation:
1. Mahatma Gandhi University, Kottayam, Kerala, India
Publisher
ACM Press
Reference26 articles.
1. Kumar, P., & Rathore, D. V. S. (2014). "Efficient capabilities of processing of big data using hadoop map reduce". International Journal of Advanced Research in Computer and Communication Engineering, 3(6), 7123--6.
2. Feldman, D., Schmidt, M., & Sohler, C. (2013, January). "Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering". In Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 1434--1453). Society for Industrial and Applied Mathematics.
3. Ha, S., Lee, S., & Lee, K. (2014). "Standardization Requirements Analysis on Big Data in Public Sector based on Potential Business Models". International Journal of Software Engineering and Its Applications, 8(11), 165--172.
4. Galit Shmueil, "To Explin or Predict?", Statistical science, vol25 © Institute of Mathematical Science, 2010
5. Saritha, K., & Abraham, S. (2017, July). "Prediction with partitioning: Big data analytics using regression techniques". In Networks & Advances in Computational Technologies (NetACT), 2017 International Conference on (pp. 208--214). IEEE.
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