HackerRank Data Scientist Hiring Test: Predict Life Expectancy
Governments, research institutes, and organizations like the United Nations and the World Bank try to
understand the relationship between the life expectancy of a country or a geographical area and
socioeconomic factors. Such analysis is valuable in deciding economic and social policies. Can you
construct a reliable model that predicts the life expectancy of an area (country, region, group of
countries) using socioeconomic variables and identify how different features influence that?
Every row of the train_data or the test_data represents socioeconomic variables of a geographical
area. That area could be a country, a group of countries, a region or a big country’s provision.
Goal:
For every row in the test data, you must predict the value of the life expectancy. The predictions must
be saved in a .csv file with the name ‘submission.csv’.
The CSV file must have two columns.
- The first column must be the index of the test set
- The second column must have the predicted value of every corresponding index value.
Evaluation Metric:
The metric used for evaluating the performance of the predictive model will be the mean absolute
error of the predictions from the ground truth (the real values of the life expectancy for every row in
the test set).
For more information please refer to the PDF file uploaded in this repo.