TY - GEN
T1 - The application of rough set and fuzzy rough set based algorithm to classify incomplete meteorological data
AU - Aprianti, Winda
AU - Mukhlash, Imam
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/3/17
Y1 - 2014/3/17
N2 - Weather has an important role in people's lives, such as agriculture, economics, socio-economic, disaster management, and finance. So, weather prediction is very important to be considered. In the prediction process we are often faced with the problem of data incompleteness. Therefore, it needs a proper classification algorithm that able to handle incomplete attribute values in the training data. In this paper, we use two approaches to handle incomplete data, namely are rough set and fuzzy rough set based algorithms. To test the performance of the two algorithms, we use meteorological data to classify rain or dry season. Conclusion of the study showed that the rough set approach is more efficient than the fuzzy rough sets approach. The advantage of fuzzy rough set approach can predict all the conditions that may occur, which can't be done by the rough set approach.
AB - Weather has an important role in people's lives, such as agriculture, economics, socio-economic, disaster management, and finance. So, weather prediction is very important to be considered. In the prediction process we are often faced with the problem of data incompleteness. Therefore, it needs a proper classification algorithm that able to handle incomplete attribute values in the training data. In this paper, we use two approaches to handle incomplete data, namely are rough set and fuzzy rough set based algorithms. To test the performance of the two algorithms, we use meteorological data to classify rain or dry season. Conclusion of the study showed that the rough set approach is more efficient than the fuzzy rough sets approach. The advantage of fuzzy rough set approach can predict all the conditions that may occur, which can't be done by the rough set approach.
KW - classification
KW - data mining
KW - fuzzy rough set
KW - incomplete data
KW - rough set
UR - http://www.scopus.com/inward/record.url?scp=84946685124&partnerID=8YFLogxK
U2 - 10.1109/ICODSE.2014.7062674
DO - 10.1109/ICODSE.2014.7062674
M3 - Conference contribution
AN - SCOPUS:84946685124
T3 - Proceedings of 2014 International Conference on Data and Software Engineering, ICODSE 2014
BT - Proceedings of 2014 International Conference on Data and Software Engineering, ICODSE 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 International Conference on Data and Software Engineering, ICODSE 2014
Y2 - 26 November 2014 through 27 November 2014
ER -