Financial Inclusion in Africa
Knowledge/Pre-Qualification to AI Hack Tunisia 2019
Who is most likely to have a bank account?
1 August–31 August 2019 23:59
356 data scientists enrolled, 152 on the leaderboard
Score calculation
published 12 Aug 2019, 11:08

Hi guys am looking for how they calculate the leaderboard

The evaluation metric for this challenge will be the percentage of survey respondents for whom you predict the binary 'bank account' classification incorrectly.

the library would be accuracy_score from sklearn

The evaluation metric is also known as misclassification rate

https://www.dataschool.io/simple-guide-to-confusion-matrix-terminology/

  • Misclassification Rate: Overall, how often is it wrong?
  • (FP+FN)/total
  • equivalent to 1 minus Accuracy
  • also known as "Error Rate"