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."
}
]
}
}
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