Fail to import MPLClassifier from SKlearn - python

I am trying to run MPL Neural Network using the scikit-learn library running on Jupyter Notebook. However, I have been trying to import the MPLClassifier but failed. I also have tried solution from here, SKlearn import MLPClassifier fails. I followed the steps and installed everything but could not import the module from SKlearn which are,
Installed the SKlearn using pip install scikit-neuralnetwork
Installed the mingw package using conda install mingw libpython and conda install -c free mingw, as the package is not available when using https://jmeubank.github.io/tdm-gcc/
Checked its availability using conda list
It is giving the following error,
cannot import name 'MPLClassifier' from 'sklearn.neural_network'
May I get help on other alternatives to import the module?

Related

Gensim package installation/word2vec not recognised

from gensim.models import Word2Vec
results in the following error
ImportError: cannot import name 'Word2Vec' from 'gensim.models' (unknown location)
from gensim.models.word2vec import Word2Vec
results in the same error
After deleting all conda installations of this package, pip uninstalling gensim, pip installing gensim and pip install --upgrade gensim, I can finally do
import gensim
but when I try to use gensim.models.Word2Vec it results in the error:
AttributeError: module 'gensim.models' has no attribute 'Word2Vec'
Edit: updated Numpy and Scipy as well
Note: I am using a jupyter notebook that I run from my local machine. I have not had this problem using Pycharm where I was running gensim from a conda env (but I'm working on a group project in notebook so it would be nice if I didn't constantly have to copy paste between these 2 workspaces...)
Any help would be appreciated
First, try to restart your kernel after the installation and see if it works. Then, check that your are in the right virtual environment. Then, please check you gensim version. In a notebook cell run
import gensim
gensim.__version__ # should be 4.1.2. If it's not update via pip.
You can also manually inspect if gensim.models.word2vec is actually there. In a notebook cell run
gensim.__path__
and go to the folder. Here you can see if there's indeed a folder named models and a script named word2vec. If not, there's something wrong with your installation. Hope this helps a bit.

sklearn.feature_selection.mutual_info_regression not found

I have been trying to utilise mutual_info_regression method from sklearn, I have updated sklearn to latest build which is 0.24.1 and when I checked the source code inside my conda env path there is folder and files for feature_selection.mutual_info_regression, but when I try to import it in my Jupiter notebook it throws this error ImportError: cannot import name 'mutual_info_regression' from 'sklearn.model_selection' (/opt/anaconda3/envs/<my_env>/lib/python3.8/site-packages/sklearn/model_selection/__init__.py)
I tried restarting kernel as well, but it is still not working, has anyone else faced this issue? Im using macOS 11.2.1 and conda 4.8.3 with Python3
Thanks
I found the solution,
I just had to restart my terminal and then it started working for some reason.
I hope this helps anyone facing such problem in future
Thanks SO!
import sklearn
print(sklearn.__version__)
Check your sklearn version sklearn.model_selection is only available for version 0.18.1
Then try this in Jupyter Notebook cell
from sklearn.feature_selection import mutual_info_regression
If any of the above doesn't work try these three steps
1- pip uninstall sklearn
2- pip uninstall scikit-learn
3- pip install sklearn

cannot import name 'haversine_distances' from 'sklearn.metrics.pairwise'

import pysal as ps
I'm tring to import pysal but I get the following:
cannot import name 'haversine_distances' from 'sklearn.metrics.pairwise'
So I tried:
from sklearn.metrics.pairwise import haversine_distances
and I get the same message.
Any suggestions?
The problem may be that your version of scikit-learn is out of date. Try uninstalling and reinstalling scikit-learn from the terminal like so:
conda uninstall scikit-learn
Confirm, and wait for the packages to be uninstalled. Then, do conda install scikit-learn and conda install pysal to reinstall the packages. You'll also need to reinstall any other packages that rely on scikit-learn as well.
I had the same issue, and this fixed the problem for me.
About scikit learn's Haversine, you have to update your scikit-learn to latest version. If you check on scikitlearn website you will find out that this module is implemented in version 0.22.1:
https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.haversine_distances.html

XGBoostError: sklearn needs to be installed in order to use this module ( GCP Datalab)

I am trying to use Xgboost in GCP datalab. I have already installed sklearn but I keep getting the error :
" XGBoostError: sklearn needs to be installed in order to use this
module"
Below is the code I used:
import sklearn
!pip3 install xgboost
from xgboost.sklearn import XGBClassifier
model = XGBClassifier()
I have tried using Python v 2.7 instead, but no luck...does anyone know how to solve this issue in GCP Datalab?
I also faced the same issue, on python 3.7 32bit on ipython.
Solution: Uninstall the xgboost package by pip uninstall xgboost on terminal/cmd. Cross-check on the your console if you cannot import it. Now again install xgboost pip install xgboost or pip install xgboost-0.81-cp37-cp37m-win32.whl, given that you have already installed sklearn, it will work on newer console session.
xgboost wheel Link: https://pypi.org/project/xgboost/#files
I got the same error with a more complicated project, after releasing a new version suddenly it failed.
luckily in my case, I had docker images for each version, and was able to use pip freeze to see what changed.
In both version I used xgboost==0.81
In the version that worked I had scikit-learn==0.21.3 and in the new version it was scikit-learn==0.22
surprisingly enough, that's now what caused the issue. I've tried to uninstall xgboost like it was suggested here and reverted scikit-learn to the version is was originally on, and still no luck.
what did cause the issue was an update of numpy from 1.17.4 to 1.18.0.
reverting it solved it for me (not sure why)
this was python 3.6 on ubuntu
For me un- then re-installing first sklearn and then xgboost did the trick

ImportError SciKit-learn

I am trying to get started with machine learning, so I have installed the packages: numpy, Scikit-learn, matplotlib, scipy. Some I have installed directly from pip with:
python -m pip install "package name"
and and others i have downloaded the binary files and then installed with pip. It shows no errors when I import matplotlib, numpy and sklearn, but when I write:
from sklearn import svm
it gives me the error:
ImportError: cannot import name 'svm'
I am on Python 3.5.1 and on Windows 10. Does anyone have any solutions?
import sklearn.svm as svm
model = svm.SVC()
....
http://scikit-learn.org/stable/modules/classes.html#module-sklearn.svm
It does seem that you didn't install it properly. Since you're on windows I would recommend using the Unofficial Windows Binaries for Python Extension Packages website to install future packages.
Make sure you also install the proper binaries as I pointed out in this post Installing scipy in Python 3.5 on 32-bit Windows 7 Machine. The windows version doesn't matter just make sure you're downloading Visual C++ 2015 redistributable package.

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