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 …

Scikit-Learn itself provides very good classes to handle categorical data. Instead of writing your custom function, you should use LabelEncoder which is specially designed for this purpose.

Reason to use scikit-learn : scikit-learn contains less boilerplate than the tensorflow implementation. Reason to use tensorflow : If running on Nvidia GPU the algorithm will be run …

9 As Alex stated, you need use to the full name of the module, uppercase is indifferent in this case. Both pip install scikit-learn==0.21.3 or pip install Scikit-learn==0.21.3 will work as I just …

I am building code on python using skimage. But I am getting import errors while using skimage.segmentation. Traceback (most recent call last): File "superpixel.py", line …

Scikit-learns model.score (X,y) calculation works on co-efficient of determination i.e R^2 is a simple function that takes model.score= (X_test,y_test). It doesn't require y_predicted value to …

2 Here is a function, printing rules of a scikit-learn decision tree under python 3 and with offsets for conditional blocks to make the structure more readable:

Pip seemed to picked that up and used it as the build system for scikit-image, causing the errors. Simply removing ninja from path solved my problem and scikit-image installed successfully.

But although scikit-learn (which contains sklearn, that was initially confusing) seems fully installed on my system, including "import sklearn" working outside of PyCharm, I could not get the …

Note upfront: I tried following suggestions in other threads, but so far, haven't found anything that helps (1, 2) I received a pandas file that I would like to run on my machine. In the beginning...