Automated Machine Learning based on Genetic Programming: a case study on a real house pricing dataset
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Masrom:2019:AiDAS,
-
author = "S. Masrom and T. Mohd and N. S. Jamil and
A. S. A. Rahman and N. Baharun",
-
title = "Automated Machine Learning based on Genetic
Programming: a case study on a real house pricing
dataset",
-
booktitle = "2019 1st International Conference on Artificial
Intelligence and Data Sciences (AiDAS)",
-
year = "2019",
-
pages = "48--52",
-
month = sep,
-
keywords = "genetic algorithms, genetic programming",
-
DOI = "doi:10.1109/AiDAS47888.2019.8970916",
-
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. demonstrates the use 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.",
-
notes = "Also known as \cite{8970916}",
- }
Genetic Programming entries for
Suraya Masrom
T Mohd
N S Jamil
A S A Rahman
Norhayati Baharun
Citations