Ashish Thanki

The question states to train a **Support Vector Regressor NOT a LinearSVR**. There is a significant difference between the two. To put it simply, imagine fitting a line of best...

Support Vector Regressors can be both linear and polynomial but the LinearSVR is only linear. > the solution of this exercise the author used LinearSVR(random_state=42) as well. He later used...

> all right, thank you very much for your kind help. > > > Has your prepared data been scaled and is the pre-processing being performed using column transformer and...

Hi @anandravishankar12 @gimseng I would like to help with this too. Perhaps we can share the workload.

Hi @cmarmo / @Micky774 can i work on this issue?

Thanks! The default value for `t_0` is not explicitly defined but is highlighted within https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/linear_model/_sgd_fast.pyx#L526 ``` if learning_rate == OPTIMAL: typw = np.sqrt(1.0 / np.sqrt(alpha)) # computing eta0, the initial...

Thanks for clarifying @Micky774 Doing a bit of a dive in the existing references I was able to confirm the formula that is being used. However, the hyperparameter `alpha` is...