steve0hh
Joined 6 years ago
Karma
42
Submissions
5
Member since
Apr 29
Random guy on the internet. Loves programming :)
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Comment · 6 years ago
Thanks for your comments.
I know the documentation and examples is still a bit raw, will be working on it.
When doing the implementation, I was trying to mimic the original API(https://github.com/bhatiasiddharth/MIDAS) that was done in the C++ first.
This was in case someone wants to use the exact same API(for familiarity) in Go, they could. Posted this here to show that there is now a Go implementation of it. :)
After this, I'll be implementing a fit/predict api that mimics SKLearn's API and showing more examples on how to use it in a streaming fashion.
Comment · 6 years ago
I adapted the code from the original paper from https://github.com/bhatiasiddharth/MIDAS/ .
And from one of the issues(https://github.com/bhatiasiddharth/MIDAS/issues/7#issuecomme...), M can be any reasonable value because it's just used to compute the edge hash (https://github.com/steve0hh/midas/blob/master/edgehash.go#L4...).
Hope it clarifies.
Comment · 6 years ago
Thanks for your comments. I'll be updating the readme to better reflect it..
I've just added the midas struct, in which you can do the following:
```
m := midas.NewMidasModel(2, 769, 9460)
m.FitPredict(2,3,1) // inputs will be your src,dst and time (from your stream)
m.FitPredict(2,3,1) // same here
```
The MidasR model is next. :)
Comment · 6 years ago
I've just added the fit/predict api for Midas.
Will be doing MidasR next when I've time. :)
The change needed is basically to create a MirasR struct and re-purpose the MidasR function into fit and predict.