Masrom, S. and Mohd, T. and Jamil, N.S. and Rahman, A.S.A. and Baharun, N. (2019) Automated machine learning based on genetic programming: A case study on a real house pricing dataset. In: UNSPECIFIED.
Full text not available from this repository.Abstract
Designing an effective machine learning model for prediction or classification problem is a tedious endeavor. Significant time and expertise are needed to customize the model for a specific problem. A significant way to reduce the complicated design is by using Automated Machine Learning (AML) that can intelligently optimize the best pipeline suitable for a problem or dataset. This paper demonstrates the utilization of an AML that has been developed with a meta-heuristic algorithm namely Genetic Programming (GP). Empirical experiment has been conducted to test the performances of AML on a real dataset of house prices in the area of Petaling Jaya, Selangor. The results show that the AML with GP able to produce the best pipeline of machine learning with high score of accuracy and minimal error. (Abstract) © 2019 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 2; Conference of 1st International Conference on Artificial Intelligence and Data Sciences, AiDAS 2019 ; Conference Date: 19 September 2019; Conference Code:157266 |
Uncontrolled Keywords: | Automation; Costs; Genetic algorithms; Heuristic algorithms; Heuristic programming; Machine learning; Pipelines; Statistical tests, Automated machines; Empirical experiments; Key words; Machine learning models; Meta heuristic algorithm; Minimal errors; Regression; Specific problems, Genetic programming |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 10 Nov 2023 03:25 |
Last Modified: | 10 Nov 2023 03:25 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/11330 |