Here is the full log (slightly different now as I was trying to reinstall several times, but still referring to the same issue). I didn't expect that installation of XGBoost can be such a huge problem. core import DMatrix, BoosterĬ:\Anaconda3\lib\site-packages\xgboost-0.4-p圓.5.egg\xgboost\core.py in ()Īnd more like this. **OSError Traceback (most recent call last)ġ2 from sklearn.cross_validation import train_test_splitĬ:\Anaconda3\lib\site-packages\xgboost-0.4-p圓.5.egg\xgboost_init_.py in () Unfortunately, after building the package, Anaconda still cannot import the XGBoost. This allowed me to create xgboost.exe and build the package finally with "python setup.py install". After trying several methods mentioned on web to build the package, with mingw32 and Visual Studio among others, I finally found this webpage which helped me: If you are working within a Jupyter Notebook and none of the above has worked for you, then it could be that your installation of Jupyter Notebooks is faulty in some way, so a reinstallation may be in order.I was trying to install XGBoost in Anaconda 3.4 (on Windows 10). Upgrade Jupyter Notebook package in Conda or Pip # Create the new environment in this directory # Check to see if the packages you require are installedįor virtual environments: # Navigate to your project directory This will provide you with a fresh start and should get rid of problems that installing other packages may have caused.įor Conda: # Create the new environment with the desired packagesĬonda create -n MY_ENV python=3.9 xgboost Therefore, one way to solve the module error for xgboost is to simply create a new environment with only the packages that you require, removing all of the bloatware that has built up over time. So, let’s make sure you have your correct environment running.įor virtual environments: source MY_ENV/bin/activateĬreate a new Conda or venv Python environment with xgboost installedĭuring the development process, a developer will likely install and update many different packages in their Python environment, which can over time cause conflicts and errors. Because of this, one common mistake developers make is that they don't activate the correct environment before they run the Python script or Jupyter Notebook. It is highly recommended that you use isolated environments when developing in Python. So let’s update the package or install it if it’s missing.įor Conda: # To install in the root environmentįor Pip: # To install in the root environmentĪctivate Conda or venv Python environment The most common reason for this error is that the xgboost package is not installed in your environment or an outdated version is installed. Upgrade or install xgboost package via Conda or Pip We can do this by running: pip install -upgrade pip Upgrade or install pip for Pythonįirst things first, let's check to see if we have the up to date version of pip installed. One sanity check is to run conda info in your terminal, which if it returns anything likely means you are using Conda. If you have not explicitly installed and activated Conda, then you are almost definitely going to be using Pip. It's important to know what you are using before we continue with the fix. It is common for developers to use either Pip or Conda for their Python package management.
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