Hello, new contributor here. I've been meaning to contribute to the library for a while now but I haven't found anything easy or clearenough for me to. While going through the source today, I noticed some possible features I could implement and would love to run it by the team here to see which is feasible and which is not.
1. More dataset benchmark. I noticed the benchmarksfolder only has benchmark on one of the datasets. MNIST. My plan is to add benchmarks for more datasets like iris, 'wine' and boston datasets. 2. Implement a Batch Gradient Descent Regressor and a Mini Batch Gradient Regressor just like the Stochastic Gradient Regressor available in the linear_model module. This is really my first attempt at contributing to the package so if there's anything i'm missing about either feature suggestions, please, do let me know.
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