Difference between scikit-learn and sklearn (now deprecated) Regarding the difference sklearn vs scikit-learn: The package "scikit-learn" is recommended to be installed using pip install scikit-learn but in your code imported using import sklearn A bit confusing, because you can also do pip install sklearn and will end up with the same scikit-learn package installed, because there is a "dummy" pypi package sklearn which will install scikit-learn for
Parameter stratify from method train_test_split (scikit Learn) I am trying to use train_test_split from package scikit Learn, but I am having trouble with parameter stratify Hereafter is the code: from sklearn import cross_validation, datasets X = iris data
ImportError: No module named sklearn (Python) - Stack Overflow I wanna use scikit-learn I have typed pip install -U scikit-learn pip3 install sklearn to install it; but when i type $ Python gt; gt; gt; import sklearn it returns ImportError: No module na
How to save a trained model by scikit-learn? - Stack Overflow I am trying to re-create the prediction of a trained model but I don't know how to save a model For example, I want to save the trained Gaussian processing regressor model and recreate the predict
VS Code: ModuleNotFoundError: No module named sklearn I am working in VS Code to run a Python script in conda environment named myenv where sklearn is already installed However when I import it and run the script I get the following error: Traceback
scikit learn - Is there a library function for Root mean square error . . . Another advantage of having this in sklearn is the sklearn implementations have a lot of additional boiler plate code to ensure the arrays are of the same shape, and includes the weights parameters and also handles multi-dimensional arrays and different 'array likes'