Skip to content

How to offer then recommendation based on the result? #9

@Jeriousman

Description

@Jeriousman

If I understood correctly, I see that pp in the result is the predicted probability of forgetting a word. So if pp is low, I should recommend a word associated with the pp as a user might have forgotten the word already. But from the result, I dont see associated word with pp. Then how can I recommend words to users?
And again, is my saying correct? (words with low pp values should be recommended)

Finally, I checked roughly the result and compared p (ground truth) and pp (prediction) and seemed to find that p and pp are quite not matching when they should. For example, when p is 0.0001 pp is 0.9999 and when p is 0.9999, pp is 0.0001. I saw this case quite often when I was skimming. But MAE shows it is very similar as your paper which means training is not broken. Is it normal that p and app are not so matching often? Should I still recommend repeating lexeme according to the pp values?

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions