Open davidbp opened 5 years ago
Do you have any guidelines for adding new estimators?
If the code depends on significant external packages, then it should be a separate package that imports ScikitLearnBase, but that's not the case with your code. Besides that, it should comply with the scikit-learn API of course, and it should be tested.
I would like to know how I could adapt it and leave it in this repo.
Sure!
so this is not done using SGD. Should we implement abstraction to be reused to fo partial_fit ?
Yes, that would be nice. But aren't there already libraries for doing SGD in Julia? I wouldn't mind adding such a dependency, if it helps to minimize the code we have to maintain.
Also FYI, I haven't developed this package recently, and some people have reported issues with testing. If you do a PR, just make sure that the relevant tests pass, but don't worry about other issues.
Hi,
Do you have any guidelines for adding new estimators?
I have implemented a multiclass perceptron
perceptron implementation
I would like to know how I could adapt it and leave it in this repo.
This is different from the perceptron in scikitlearn (python) since this implementation natively supports multiclass (it's not using a one vs all). The main benefit is that this is faster than the sklearn version.
I looked at the native linear_regression implementation. It seems you solved directly with this line
so this is not done using SGD. Should we implement abstraction to be reused to do
partial_fit
?