mlens.parallel.evaluation module

ML-ENSEMBLE

author:Sebastian Flennerhag
copyright:2017
licence:MIT

Cross-validation jobs for an Evaluator instance.

class mlens.parallel.evaluation.Evaluation(evaluator)[source]

Bases: object

Evaluation engine.

Run a job for an Evaluator instance.

Parameters:evaluator (Evaluator) – Evaluator instance to run job for.
evaluate(parallel, X, y, dir)[source]

cross-validation of estimators.

Parameters:
  • parallel (joblib.Parallel) – The instance to use for parallel fitting.
  • X (array-like of shape [n_samples, n_features]) – Training set to use for estimation. Can be memmaped.
  • y (array-like of shape [n_samples, ]) – labels for estimation. Can be memmaped.
  • dir (str) – directory of cache to dump fitted transformers before assembly.
preprocess(parallel, X, y, dir)[source]

Fit preprocessing pipelines.

Fit all preprocessing pipelines in parallel and store as a preprocessing_ attribute on the Evaluator.

Parameters:
  • parallel (joblib.Parallel) – The instance to use for parallel fitting.
  • X (array-like of shape [n_samples, n_features]) – Training set to use for estimation. Can be memmaped.
  • y (array-like of shape [n_samples, ]) – labels for estimation. Can be memmaped.
  • dir (directory of cache to dump fitted transformers before assembly.) –
mlens.parallel.evaluation.fit_score(case, tr_list, est_name, est, params, x, y, idx, scorer, error_score)[source]

Wrapper around fit function to determine how to handle exceptions.