> 418 output=stdout, stderr=stderr) 419 return CompletedProcess (process. > 336 **kwargs).stdout 337 338 C:\Program Files\Alteryx\bin\Miniconda3\lib\subprocess.py in run (input, timeout, check, *popenargs, **kwargs) 416 if check and retcode : 417 raise CalledProcessError(retcode, process.args, STDOUTĤ3 if debug : C:\Program Files\Alteryx\bin\Miniconda3\lib\subprocess.py in check_output (timeout, *popenargs, **kwargs) 334 335 return run(*popenargs, stdout=PIPE, timeout=timeout, check=True,
Create a quick and dirty classification model using XGBoost and its default parameters. > 153 _installPackages_ (package, install_type =install_type, debug =debug, **kwargs ) 154 155 c:\program files\alteryx\bin\miniconda3\pythontool_venv\lib\site-packages\ayx\Package.py in installPackages (package, install_type, debug) 112 print (pip_install_result ) 113 if not pip_install_result : -> 114 raise pip_install_result c:\program files\alteryx\bin\miniconda3\pythontool_venv\lib\site-packages\ayx\Utils.py in runSubprocess (args_list, debug) 39 result = subprocess.check_output(Ĥ0 args_list, -> 41 stderr = subprocess. Configuring XGBoost to use your GPU Once you have the CUDA toolkit installed (Ubuntu user’s can follow this guide ), you then need to install XGBoost with CUDA support (I think this worked out of the box on my machine). If using an admin installation of Alteryx, you must run Alteryx as administrator in order to use this function and install packages. installPackages ( "xgboost=0.71" ) 3 4 # First XGBoost model for Pima Indians dataset 5 from numpy import loadtxtĬ:\program files\alteryx\bin\miniconda3\pythontool_venv\lib\site-packages\ayx\export.py in installPackage (package, install_type, debug, **kwargs) 151 This function will install a package or list of packages into the virtual environment used by the Python tool. CalledProcessError Traceback (most recent call last)
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