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Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library
Nonsense, since there is no train-val set split. Sample_idxs is for training only, so it doesn't matter if time-related features' order is mixed, since they will be sorted anyway when choosing best split
Fixing Adam+L2 with AdamW by adding weight decay term AFTER the exponentially moving average for grad_w.
Remove line 97 and change line 100 to self.weights[i][0]-= lr*(grad_w + (l2/bs) * self.weights[i][0])
Related article on AdamW: https://towardsdatascience.com/why-adamw-matters-736223f31b5d
inp is (wx + b), activation is act(inp) or act(wx+b)
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