The model fit of my SGDRegressor wont increase or decrease its performance on the validation set (test) after around 20’000 training records. Even if I try to switch penalty, early_stopping (True/…

The model fit of my SGDRegressor wont increase or decrease its performance on the validation set (test) after around 20’000 training records. Even if I try to switch penalty, early_stopping (True/…

Can we do log transform to one variable and sqrt to another for LinearRegression? If yes then what to do during MSE? Should I exp or square the y_test and prediction? boston[‘medv_log’] = np.log(…

The code below creates a regression line; however, the legend defaults to labeling the line as “undefined.” How can this regression line be labeled in the legend as “reg-line”? …

I am trying to create a multiple linear regression model from scratch in python. Dataset used: Boston Housing Dataset from Sklearn. Since my focus was on the model building I did not perform any pre-…

What’s the cleanest, most pythonic way to run a regression only on non-missing data and use clustered standard errors? Imagine I have a Pandas dataframe all_data. Clunky method that works (make a dataframe without missing data): I can make a new dataframe without the missing data, make the model, and fit the model: This feels a bit clunky (esp. when I’m doing it all over the place with different right hand side variables.) And I have to make sure that my stats formula matches the dataframe variables. But is there a way to make it work using the missing argument?