Global configurationsΒΆ

ML-Ensemble allows a set of low-level global configurations to tailor the behavior of classes during estimation. Every variable is accessible through mlens.config. Alternatively, all variables can be set as global environmental variables, where the exported variable name is MLENS_[VARNAME].

  • mlens.config.BACKEND
    configures the global default backend during parallelized estimation. Default is 'threading'. Options are 'multiprocessing' and 'forkserver'. See joblib for further information. Alter with the set_backend function.
  • mlens.config.DTYPE
    determines the default dtype of numpy arrays created during estimation; in particular, the prediction matrices of each intermediate layer. Default is numpy.float32. Alter with the set_backend function.
  • mlens.config.TMPDIR
    The directory where temporary folders are created during estimation. Default uses the tempfile function gettempdir(). Alter with the set_backend function.
  • mlens.config.START_METHOD
    The method used by the job manager to generate a new job. ML-Ensemble defaults to forkserver``on Unix with Python 3.4+, and ``spawn on windows. For older Python versions, the default is fork. This method has the least overhead, but it can cause issues with third-party software. See Bad interaction with third-party packages for details. Set this variable with the set_start_method function.