@inproceedings{ee4ef819081e4a78a11f6e0d010135c4,
title = "MIC for Analyzing Attributes Associated with Thai Agricultural Products",
abstract = "A prediction system of Thai agricultural products will purpose as our future work. The large amount of data is necessary and precise to predict the trend. Due to the high-efficiency prediction, only the associated attributes are preferred and well prepared in the next process. MIC is one statistical method to measure a correlation coefficient of pairwise variables on an immense dataset. After that their correlation coefficient shows the ranking of variables relationship. Thus, the pre-processing of data is done before executing. In this paper will present the theoretical of MIC and related works. The general concepts of MIC and the special ideas will be described.",
keywords = "Agricultural production, MIC, Prediction production",
author = "Tisinee Surapunt and Chuanlu Liu and Shuliang Wang",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 ; Conference date: 08-12-2017 Through 10-12-2017",
year = "2018",
doi = "10.1007/978-981-13-0893-2_5",
language = "English",
isbn = "9789811308925",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "40--47",
editor = "Fuling Bian and Hanning Yuan and Jing Geng and Chuanlu Liu and Tisinee Surapunt",
booktitle = "Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers",
address = "Germany",
}
