Recentness biased learning for time series forecasting

Inf. Sci., pp. 29-38, 2013.

Cited by: 13|Bibtex|Views6|DOI:https://doi.org/10.1016/j.ins.2010.09.004
WOS SCOPUS EI
Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com|www.sciencedirect.com

Abstract:

In recent years, dynamic time series analysis with the concept drift has become an important and challenging task for a wide range of applications including stock price forecasting, target sales, etc. In this paper, a recentness biased learning method is proposed for dynamic time series analysis by introducing a drift factor. First of all...More

Code:

Data:

Your rating :
0

 

Tags
Comments