This is a practice competition to create a predictive model by using a practical data.
The data is related with direct marketing campaigns and actually used in the practical field. Try out your skills to create a better model than the existing benchmark model proposed in the paper.
We hope this competition will be a good opportunity for expanding your data science skills and modeling techniques.
The data is related with direct marketing campaigns of a certain banking institution. The classification goal is to predict if the client will subscribe (yes/no) a term deposit.
Number of explanatory variables are 16 and both train and test set contain these variables and only test set contains the target variable.
Please see Download Data page for details.
This competition uses data sited from the following website and paper:
Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.
[Moro et al., 2011] S. Moro, R. Laureano and P. Cortez. Using Data Mining for Bank Direct Marketing: An Application of the CRISP-DM Methodology. In P. Novais et al. (Eds.), Proceedings of the European Simulation and Modelling Conference - ESM'2011, pp. 117-121, GuimarÃ£es, Portugal, October, 2011. EUROSIS.