In this challenge, your task is to develop a multi-class classification model to identify and classify faults according to their categories specified. The model can be used by AirQo to automatically flag a device that is returning faulty data.
The train file contains approximately 300 000 readings and the test contains approximately 100 000 readings.
There are missing values in this data so think about how you would go about tackling them.
Files
Description
Files
This shows the submission format for this competition, with the ‘ID’ column mirroring that of Test.csv and the ‘Signal’ column containing your predictions. The order of the rows does not matter, but the names of the ‘ID’ must be correct.
This is the dataset that you will use to train your model, it contains the target.
This is the dataset on which you will apply your model to, it resembles Train.csv but without the target column.
This will help you make your first submission on the leaderboard.
