Fisher Score-Based Feature Selection for Ordinal Classification: A Social Survey on Subjective Well-Being
This paper approaches the problem of feature selection in the context of ordinal classification problems. To do so, an ordinal version of the Fisher score is proposed. We test this new strategy considering data from an European social survey concerning subjective well-being, in order to understand and identify the most important variables for a person’s happiness, which is represented using ordered categories. The input variables have been chosen according to previous research, and these have been categorised in the following groups: demographics, daily activities, social well-being, health and habits, community well-being and personality/opinion. The proposed strategy shows promising results and performs significantly better than its nominal counterpart, therefore validating the need of developing specific ordinal feature selection methods. Furthermore, the results of this paper can shed some light on the human psyche by analysing the most and less frequently selected variables.
KeywordsFeature Selection Feature Selection Method Hausdorff Distance Mean Absolute Error European Social Survey
- 3.Self, A., Thomas, J., Randall, C.: Measuring national well-being: Life in the uk (2012). Accessed 8 December 2015Google Scholar
- 6.Gu, Q., Li, Z., Han, J.: Generalized fisher score for feature selection. CoRR abs/1202.3725 (2012)Google Scholar
- 11.Mukras, R., Wiratunga, N., Lothian, R., Chakraborti, S., Harper, D.: Information gain feature selection for ordinal text classification using probability re-distribution. In: The IJCAI 2007 Workshop on Text Mining and Link Analysis, Hyderabad, IN (2007)Google Scholar
- 14.Baccianella, S., Esuli, A., Sebastiani, F.: Evaluation measures for ordinal regression. In: Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications (ISDA 2009), Pisa, Italy (2009)Google Scholar