Jan-10-2021, 11:53 AM
(This post was last modified: Jan-10-2021, 11:53 AM by HoldYourBreath.)
hi, i just want to learn differences between scalar.fit command with differant coulumns
becuse in general programmers use just fit with 1 column and transform it all the others. i dont understand the point. thank you
becuse in general programmers use just fit with 1 column and transform it all the others. i dont understand the point. thank you
from sklearn.preprocessing import MinMaxScaler scaler = MinMaxScaler() scaler2 = MinMaxScaler() scaler3 = MinMaxScaler() #programmers use this, why transform x_test to x_test2 with "scaler.fit(x_train)" scaler.fit(x_train) x_train = scaler.transform(x_train) x_test2 = scaler.transform (x_test) #i think this one better but i dont know why pros didnt use it? scaler2.fit(x_test) x_test3=scaler2.transform(x_test)
Larz60+ write Jan-10-2021, 10:44 AM:
Please post all code, output and errors (it it's entirety) between their respective tags. Refer to BBCode help topic on how to post. Use the "Preview Post" button to make sure the code is presented as you expect before hitting the "Post Reply/Thread" button.
Fixed for you this time. Please use code tags on future posts.
Please post all code, output and errors (it it's entirety) between their respective tags. Refer to BBCode help topic on how to post. Use the "Preview Post" button to make sure the code is presented as you expect before hitting the "Post Reply/Thread" button.
Fixed for you this time. Please use code tags on future posts.
