Citazione: V. Di Lecce, A. Amato, M. Calabrese, Decision Trees in Time Series Reconstruction Problems, I2MTC 2008 - IEEE International Instrumentation and Measurement Technology Conference, Vancouver, Canada, pp. 895 - 899, May 12-15, 2008. (ISSN: 1091-5281 ISBN: 978-1-4244-1540-3)
Abstract: This work proposes to use a decision tree classifier for time series data reconstruction. Object of this analysis is to study environmental data acquired by a distributed multi-sensors monitoring system placed in Taranto. The performance obtained in data reconstruction using the proposed decision tree is compared with those obtained using two well known signal reconstruction methods: mean value and polynomial interpolation. The results show that the decision tree outperforms the other two methods in almost all the analyzed cases.
Keyword: time series data reconstruction, decision tree, polynomial interpolation, measurement of environmental data