Publications:A novel approach to designing an adaptive committee applied to predicting company's future performance

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Title A novel approach to designing an adaptive committee applied to predicting company’s future performance
Author Zivile Kalsyte and Antanas Verikas and Marija Bacauskiene and Adas Gelzinis
Year 2013
PublicationType Journal Paper
Journal Expert systems with applications
HostPublication
Conference
DOI http://dx.doi.org/10.1016/j.eswa.2012.10.018
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:630760
Abstract This article presents an approach to designing an adaptive, data dependent, committee of models applied to prediction of several financial attributes for assessing company's future performance. Current liabilities/Current assets, Total liabilities/Total assets, Net income/Total assets, and Operating Income/Total liabilities are the attributes used in this paper. A self-organizing map (SOM) used for data mapping and analysis enables building committees, which are specific (committee size and aggregation weights) for each SOM node. The number of basic models aggregated into a committee and the aggregation weights depend on accuracy of basic models and their ability to generalize in the vicinity of the SOM node. A random forest is used a basic model in this study. The developed technique was tested on data concerning companies from ten sectors of the healthcare industry of the United States and compared with results obtained from averaging and weighted averaging committees. The proposed adaptivity of a committee size and aggregation weights led to a statistically significant increase in prediction accuracy if compared to other types of committees. © 2012 Elsevier Ltd. All rights reserved.