compare_classifiers.ensemble_compare_f1
=======================================

.. py:module:: compare_classifiers.ensemble_compare_f1


Functions
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.. autoapisummary::

   compare_classifiers.ensemble_compare_f1.ensemble_compare_f1


Module Contents
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.. py:function:: ensemble_compare_f1(estimators, X_train, y_train)

   Show cross validation results, including fit time and f1 scores by stacking and voting the estimators.

   :param estimators: A list of (name, estimator) tuples, consisting of individual estimators to be processed through the voting or stacking classifying ensemble. Each tuple contains a string: name/label of estimator, and a model: the estimator, which implements
                      the scikit-learn API (`fit`, `predict`, etc.).
   :type estimators: list of tuples
   :param X_train: Data frame containing training data along with n features or ndarray with no feature names.
   :type X_train: Pandas data frame
   :param y_train: Target class labels for data in X_train.
   :type y_train: Pandas series or Numpy array

   :returns: A data frame showing cross validation results on training data, with 3 columns: fit_time, test_score, train_score and 2 rows: voting, stacking.
   :rtype: Pandas data frame

   .. rubric:: Examples

   >>> estimators = [
   ...     ('rf', RandomForestClassifier(n_estimators=10, random_state=42)),
   ...     ('svm', make_pipeline(StandardScaler(), LinearSVC(random_state=42)))
   ... ]
   >>> ensemble_compare_f1(estimators, X, y)