Xente Fraud Detection Challenge
$4,500 USD
Accurately classify the fraudulent transactions from Xente's e-commerce platform
20 May–22 September 2019 23:59
1103 data scientists enrolled, 547 on the leaderboard
Submission
published 25 May 2019, 00:25

Hi! I made my first submission and got a score of 0. Is it that the predicted target variables are to be changed into a new data type(e.g float or string) before submission?

no i have also had a score of zero once its because of the metric used f1 score

The F-measure is the harmonic mean of your precision and recall. In most situations, you have a trade-off between precision and recall. If you optimize your classifier to increase one and disfavor the other, the harmonic mean quickly decreases. It is greatest however, when both precision and recall are equal.

How did you get to resolve this problem

Hi, have you been able to resolve this problem ?

The datasets is really imbalanced i tried so many things ranging from trying to make it balance and some features engineering taking a look at the datasets you would observe from some critical visualization that you are predicting for the future meaning the test sets is not part of the time for the train so surely it would take some rigorous process of understanding how and what to do to achieve a good results.