I imported a data set with a field with "timestamp" data in seconds as shown below. I would like to do time aware modelling. However, datarobot could not detect any time features in the dataset. Later, I found in the feature list that, datarobot automatically eliminated "timestamp" saying, [too many values, Reference ID] due to which, I am not able to do timeaware modelling. Any help in solving this issue will be highly appreciated.
That is a great question!
One reason why DataRobot was not considering this column as a time column is its format. Try changing the format of the values in this column to YYY-MM-DD HH:MM or YYYY-MM-DD HH:MM:SS.
Thanks @Lukas and @rtungaraza for the solution. Now I have my timestamp in format (see below). Even now, DR cannot identify time feature. The timestamp column is still not available as a feature saying, it has "too many values". I am stuck at this point unable to do any further analysis.
Thanks @Lukas for the the solution. It looks like the problem is with something else. DR is not able to take the time as a feature because of which it is not recognized during Time-aware modelling. DR is eliminating the time feature saying too many values.
I tried another file with timestamp in the following format and it worked. Now I need to solve this "too many values" issue.
@nsahoo3 Yes, the problem here is the number of time-steps. If you include fine-grained time information, then the step size is going to be at the most granular level represented in your data (seconds).
What granularity of data do you want to model? Daily, hourly, minute, second, etc? You may need to aggregate your data into your granularity of interest, split your date-time column into a date and time columns (if you want daily or larger granularity), or reduce the duration of your training data for building the initial project (if you want sub-day granularity).