I have already (in another machine) installed scikit-learn (with pip) and then tensor-flow and they both worked fine.Īlso when i am using anaconda as channel parameter (i.e.

The documentation for install says 'To prevent existing packages from updating, use the -freeze-installed option.' however, it doesn't work and already existing packages still change.

And finally the most import one: how can I prevent this? how cant i force conda not to change the already existing packages and find the version of scikit-learn compatible with the current environment.

Why some already existing packages with similar version numbers are also downloaded again?.

Answer: it maybe due to the fact that tensor-flow is installed with pip not conda If full compatibility cannot be assured, an error is reported and the environment is not changed'.

Shouldn't conda automatically prevent this? because the documentation for install says: ' installs a set of packages consistent with those specifications and compatible with the underlying environment.

There are other packages that are also updated and some of them still downloading the same version like certifi-2023.5.7! Numpy 1.23.5 -> is updated to numpy-1.24.3 (and tensor-flow have problems with this version)Ĭharset-normalizer is also changed to charset-normalizer-2.0.4 (which also causes issues) the problem is that some packages are updated, which are inconsistent with the current version of tensorflow (for instance) : after a while, i wanted to install scikit-learn (with conda in the same environment), however tensorflow stopped working. I have installed tensorflow (the last version), and it works perfectly.

Conda install sklearn