From d117816199f7d05ddc085d9fa197b90b0587c722 Mon Sep 17 00:00:00 2001 From: Hanmin Qin Date: Fri, 10 Nov 2017 09:17:00 +0800 Subject: [PATCH] fix dead link --- doc/whats_new/v0.20.rst | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/doc/whats_new/v0.20.rst b/doc/whats_new/v0.20.rst index 0897f331ebda0..fd0ce46db2576 100644 --- a/doc/whats_new/v0.20.rst +++ b/doc/whats_new/v0.20.rst @@ -46,7 +46,7 @@ Classifiers and regressors Model evaluation -- Added the :func:`metrics.balanced_accuracy` metric and a corresponding +- Added the :func:`metrics.balanced_accuracy_score` metric and a corresponding ``'balanced_accuracy'`` scorer for binary classification. :issue:`8066` by :user:`xyguo` and :user:`Aman Dalmia `. @@ -61,11 +61,11 @@ Classifiers and regressors and :user:`Minghui Liu `. - Add `named_estimators_` parameter in - :class:`sklearn.ensemble.voting_classifier` to access fitted + :class:`ensemble.VotingClassifier` to access fitted estimators. :issue:`9157` by :user:`Herilalaina Rakotoarison `. - Add `var_smoothing` parameter in - :class:`sklearn.naive_bayes.GaussianNB` to give a precise control over + :class:`naive_bayes.GaussianNB` to give a precise control over variances calculation. :issue:`9681` by :user:`Dmitry Mottl `. - Add `n_iter_no_change` parameter in @@ -75,9 +75,9 @@ Classifiers and regressors maximum number of epochs to not meet ``tol`` improvement. :issue:`9456` by :user:`Nicholas Nadeau `. -- A parameter ``check_inverse`` was added to :class:`FunctionTransformer` - to ensure that ``func`` and ``inverse_func`` are the inverse of each - other. +- A parameter ``check_inverse`` was added to + :class:`preprocessing.FunctionTransformer` to ensure that ``func`` and + ``inverse_func`` are the inverse of each other. :issue:`9399` by :user:`Guillaume Lemaitre `. Model evaluation and meta-estimators @@ -133,7 +133,7 @@ Decomposition, manifold learning and clustering :user:`James Bourbeau `. - Fixed a bug where the ``fit`` method of - :class:`cluster.affinity_propagation_.AffinityPropagation` stored cluster + :class:`cluster.AffinityPropagation` stored cluster centers as 3d array instead of 2d array in case of non-convergence. For the same class, fixed undefined and arbitrary behavior in case of training data where all samples had equal similarity.