Pushing the docs to dev/ for branch: master, commit e8a364b471edc1f5d54c3e6a90696578db3f7171

Author: sklearn-ci

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -341,7 +341,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "#### References:\n.. [1] Dietterich, T. G. (1998). `Approximate statistical tests for comparing\n       supervised classification learning algorithms\n       <http://web.cs.iastate.edu/~jtian/cs573/Papers/Dietterich-98.pdf>`_.\n       Neural computation, 10(7).\n.. [2] Nadeau, C., & Bengio, Y. (2000). `Inference for the generalization\n       error\n       <https://papers.nips.cc/paper/1661-inference-for-the-generalization-error.pdf>`_.\n       In Advances in neural information processing systems.\n.. [3] Bouckaert, R. R., & Frank, E. (2004). `Evaluating the replicability of\n       significance tests for comparing learning algorithms\n       <https://www.cms.waikato.ac.nz/~ml/publications/2004/bouckaert-frank.pdf>`_.\n       In Pacific-Asia Conference on Knowledge Discovery and Data Mining.\n.. [4] Benavoli, A., Corani, G., Dem\u0161ar, J., & Zaffalon, M. (2017). `Time for\n       a change: a tutorial for comparing multiple classifiers through\n       Bayesian analysis\n       <http://www.jmlr.org/papers/volume18/16-305/16-305.pdf>`_.\n       The Journal of Machine Learning Research, 18(1). See the Python\n       library that accompanies this paper `here\n       <https://github.com/janezd/baycomp>`_.\n.. [5] Diebold, F.X. & Mariano R.S. (1995). `Comparing predictive accuracy\n       <http://www.est.uc3m.es/esp/nueva_docencia/comp_col_get/lade/tecnicas_prediccion/Practicas0708/Comparing%20Predictive%20Accuracy%20(Dielbold).pdf>`_\n       Journal of Business & economic statistics, 20(1), 134-144.\n\n"
+        ".. topic:: References\n\n   .. [1] Dietterich, T. G. (1998). `Approximate statistical tests for\n          comparing supervised classification learning algorithms\n          <http://web.cs.iastate.edu/~jtian/cs573/Papers/Dietterich-98.pdf>`_.\n          Neural computation, 10(7).\n   .. [2] Nadeau, C., & Bengio, Y. (2000). `Inference for the generalization\n          error\n          <https://papers.nips.cc/paper/1661-inference-for-the-generalization-error.pdf>`_.\n          In Advances in neural information processing systems.\n   .. [3] Bouckaert, R. R., & Frank, E. (2004). `Evaluating the replicability\n          of significance tests for comparing learning algorithms\n          <https://www.cms.waikato.ac.nz/~ml/publications/2004/bouckaert-frank.pdf>`_.\n          In Pacific-Asia Conference on Knowledge Discovery and Data Mining.\n   .. [4] Benavoli, A., Corani, G., Dem\u0161ar, J., & Zaffalon, M. (2017). `Time\n          for a change: a tutorial for comparing multiple classifiers through\n          Bayesian analysis\n          <http://www.jmlr.org/papers/volume18/16-305/16-305.pdf>`_.\n          The Journal of Machine Learning Research, 18(1). See the Python\n          library that accompanies this paper `here\n          <https://github.com/janezd/baycomp>`_.\n   .. [5] Diebold, F.X. & Mariano R.S. (1995). `Comparing predictive accuracy\n          <http://www.est.uc3m.es/esp/nueva_docencia/comp_col_get/lade/tecnicas_prediccion/Practicas0708/Comparing%20Predictive%20Accuracy%20(Dielbold).pdf>`_\n          Journal of Business & economic statistics, 20(1), 134-144.\n\n"
       ]
     }
   ],

dev/_downloads/2402de18d671ce5087e3760b2540184f/plot_grid_search_stats.ipynb

@@ -551,27 +551,27 @@ def compute_corrected_ttest(differences, df, n_train, n_test):
 #   correction is needed when using the frequentist approach.
 
 # %%
-# References:
-# ___________
-# .. [1] Dietterich, T. G. (1998). `Approximate statistical tests for comparing
-#        supervised classification learning algorithms
-#        <http://web.cs.iastate.edu/~jtian/cs573/Papers/Dietterich-98.pdf>`_.
-#        Neural computation, 10(7).
-# .. [2] Nadeau, C., & Bengio, Y. (2000). `Inference for the generalization
-#        error
-#        <https://papers.nips.cc/paper/1661-inference-for-the-generalization-error.pdf>`_.
-#        In Advances in neural information processing systems.
-# .. [3] Bouckaert, R. R., & Frank, E. (2004). `Evaluating the replicability of
-#        significance tests for comparing learning algorithms
-#        <https://www.cms.waikato.ac.nz/~ml/publications/2004/bouckaert-frank.pdf>`_.
-#        In Pacific-Asia Conference on Knowledge Discovery and Data Mining.
-# .. [4] Benavoli, A., Corani, G., Demšar, J., & Zaffalon, M. (2017). `Time for
-#        a change: a tutorial for comparing multiple classifiers through
-#        Bayesian analysis
-#        <http://www.jmlr.org/papers/volume18/16-305/16-305.pdf>`_.
-#        The Journal of Machine Learning Research, 18(1). See the Python
-#        library that accompanies this paper `here
-#        <https://github.com/janezd/baycomp>`_.
-# .. [5] Diebold, F.X. & Mariano R.S. (1995). `Comparing predictive accuracy
-#        <http://www.est.uc3m.es/esp/nueva_docencia/comp_col_get/lade/tecnicas_prediccion/Practicas0708/Comparing%20Predictive%20Accuracy%20(Dielbold).pdf>`_
-#        Journal of Business & economic statistics, 20(1), 134-144.
+# .. topic:: References
+#
+#    .. [1] Dietterich, T. G. (1998). `Approximate statistical tests for
+#           comparing supervised classification learning algorithms
+#           <http://web.cs.iastate.edu/~jtian/cs573/Papers/Dietterich-98.pdf>`_.
+#           Neural computation, 10(7).
+#    .. [2] Nadeau, C., & Bengio, Y. (2000). `Inference for the generalization
+#           error
+#           <https://papers.nips.cc/paper/1661-inference-for-the-generalization-error.pdf>`_.
+#           In Advances in neural information processing systems.
+#    .. [3] Bouckaert, R. R., & Frank, E. (2004). `Evaluating the replicability
+#           of significance tests for comparing learning algorithms
+#           <https://www.cms.waikato.ac.nz/~ml/publications/2004/bouckaert-frank.pdf>`_.
+#           In Pacific-Asia Conference on Knowledge Discovery and Data Mining.
+#    .. [4] Benavoli, A., Corani, G., Demšar, J., & Zaffalon, M. (2017). `Time
+#           for a change: a tutorial for comparing multiple classifiers through
+#           Bayesian analysis
+#           <http://www.jmlr.org/papers/volume18/16-305/16-305.pdf>`_.
+#           The Journal of Machine Learning Research, 18(1). See the Python
+#           library that accompanies this paper `here
+#           <https://github.com/janezd/baycomp>`_.
+#    .. [5] Diebold, F.X. & Mariano R.S. (1995). `Comparing predictive accuracy
+#           <http://www.est.uc3m.es/esp/nueva_docencia/comp_col_get/lade/tecnicas_prediccion/Practicas0708/Comparing%20Predictive%20Accuracy%20(Dielbold).pdf>`_
+#           Journal of Business & economic statistics, 20(1), 134-144.