Normalize line endings and whitespace

doc/tutorials/ml/table_of_content_ml/table_of_content_ml.rst

@@ -1,56 +1,56 @@
-.. _Table-Of-Content-Ml:
-
-*ml* module. Machine Learning
------------------------------------------------------------
-
-Use the powerfull machine learning classes for statistical classification, regression and clustering of data.
-
-.. include:: ../../definitions/tocDefinitions.rst 
-
-+ 
-  .. tabularcolumns:: m{100pt} m{300pt}
-  .. cssclass:: toctableopencv
-
-  ============ ==============================================
-  |IntroSVM|   **Title:** :ref:`introductiontosvms`
-
-               *Compatibility:* > OpenCV 2.0
-
-               *Author:* |Author_FernandoI|
-
-               Learn what a Suport Vector Machine is. 
-
-  ============ ==============================================
-
-  .. |IntroSVM| image:: images/introduction_to_svm.png
-     :height: 90pt
-     :width:  90pt
-
-+ 
-  .. tabularcolumns:: m{100pt} m{300pt}
-  .. cssclass:: toctableopencv
-
-  ============ ==============================================
-  |NonLinSVM|  **Title:** :ref:`nonLinearSvmS`
-
-               *Compatibility:* > OpenCV 2.0
-
-               *Author:* |Author_FernandoI|
-
-               Here you will learn how to define the optimization problem for SVMs when it is not possible to separate linearly the training data.
-
-  ============ ==============================================
-
-  .. |NonLinSVM| image:: images/non_linear_svms.png
-     :height: 90pt
-     :width:  90pt
-
-.. raw:: latex
-
-   \pagebreak
-
-.. toctree::
-   :hidden:
-   
-   ../introduction_to_svm/introduction_to_svm
-   ../non_linear_svms/non_linear_svms
+.. _Table-Of-Content-Ml:
+
+*ml* module. Machine Learning
+-----------------------------------------------------------
+
+Use the powerfull machine learning classes for statistical classification, regression and clustering of data.
+
+.. include:: ../../definitions/tocDefinitions.rst 
+
++ 
+  .. tabularcolumns:: m{100pt} m{300pt}
+  .. cssclass:: toctableopencv
+
+  ============ ==============================================
+  |IntroSVM|   **Title:** :ref:`introductiontosvms`
+
+               *Compatibility:* > OpenCV 2.0
+
+               *Author:* |Author_FernandoI|
+
+               Learn what a Suport Vector Machine is. 
+
+  ============ ==============================================
+
+  .. |IntroSVM| image:: images/introduction_to_svm.png
+     :height: 90pt
+     :width:  90pt
+
++ 
+  .. tabularcolumns:: m{100pt} m{300pt}
+  .. cssclass:: toctableopencv
+
+  ============ ==============================================
+  |NonLinSVM|  **Title:** :ref:`nonLinearSvmS`
+
+               *Compatibility:* > OpenCV 2.0
+
+               *Author:* |Author_FernandoI|
+
+               Here you will learn how to define the optimization problem for SVMs when it is not possible to separate linearly the training data.
+
+  ============ ==============================================
+
+  .. |NonLinSVM| image:: images/non_linear_svms.png
+     :height: 90pt
+     :width:  90pt
+
+.. raw:: latex
+
+   \pagebreak
+
+.. toctree::
+   :hidden:
+   
+   ../introduction_to_svm/introduction_to_svm
+   ../non_linear_svms/non_linear_svms