Predicting a users next action based on current day and time

Question

I'm using Microsoft Azure Machine Learning Studio to try an experiment where I use previous analytics captured about a user (at a time, on a day) to try and predict their next action (based on day and time) so that I can adjust the UI accordingly. So if a user normally visits a certain page every Thursday at 1 pm, then I would like to predict that behavior.

Warning - I am a complete novice with ML, but I have watched quite a few videos and worked through tutorials like the movie recommendations example.

I have a CSV dataset with userid, action, DateTime and would like to train a matchbox recommendation model, which, from my research appears to be the best model to use. I can't see a way to use date/time in the training. The idea being that if I could pass in a userid and the date, then the recommendation model should be able to give me a probable result of what that user is most likely to do.

I get results from the predictive endpoint, but the training endpoint gives the following error:

{

    "error": {

        "code": "ModuleExecutionError",

        "message": "Module execution encountered an error.",

        "details": [

            {

                "code": "18",

                "target": "Train Matchbox Recommender",

                "message": "Error 0018: Training dataset of user-item-rating triples contains invalid data."

            }

        ]

    }

}

Answer 1

Error 0018 occurs when the following happens:

1. Label column absent  or no column is selected

2. Your data is not numeric or categorical

3. Wrong format of data

4. The data imported has invalid characters  or values that are out of range

Be sure to clean your data.

Check this blog for more details.