compare_classifiers.compare_f1
==============================

.. py:module:: compare_classifiers.compare_f1


Functions
---------

.. autoapisummary::

   compare_classifiers.compare_f1.compare_f1


Module Contents
---------------

.. py:function:: compare_f1(estimators, X_train, y_train)

   Show cross validation results, including fit time and f1 scores for each estimator.

   :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 or Numpy array
   :param y_train: Target class labels for data in X_train.
   :type y_train: Pandas series or Numpy array
   :param Returns:
   :param --------:
   :param Pandas data frame: A data frame showing cross validation results on training data, with 3 columns: fit_time, test_score, train_score and 1 rows for each estimator.
   :param Example:
   :param --------:
   :param >>> estimators = [:
   :param ...     ('rf':
   :param RandomForestClassifier(n_estimators=10:
   :param random_state=42)):
   :param :
   :param ...     ('svm':
   :param make_pipeline(StandardScaler():
   :param LinearSVC(random_state=42))):
   :param ... ]:
   :param >>> compare_f1(estimators:
   :param X:
   :param y):