The World Bank competition will supply a set of training data with anonymized qualitative variables from household surveys in 3 countries, including the “poor” or “not poor” classification for each observation.
The challenge is to build models which can accurately classify households from a different set of test data (with the poor/not poor classification removed!) for the same 3 countries, and then submit them for scoring. Performance is measured by the mean log loss for the 3 countries which tells us how accurate the classification models developed are.
- plus a $2,500 bonus prize for the top-performing entry from a low- or lower-middle income country.
DEADLINE: February 28, 2018