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EKM.  Instead, the load() function now will accept non-empty lisf objects
and throw a non-fatal exception.  This behavior should be slightly less
surprising to users, especially since certain degenerate datasets can give
rise to empty lisf objects when you might not expect it.

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algorithms in dlib.  This first version was created by Gregory Sharp.

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rename : docs/htmlify/CMakeLists.txt => tools/htmlify/CMakeLists.txt
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rename : docs/htmlify/to_xml_example/bigplus.gif => tools/htmlify/to_xml_example/bigplus.gif
rename : docs/htmlify/to_xml_example/example.xml => tools/htmlify/to_xml_example/example.xml
rename : docs/htmlify/to_xml_example/minus.gif => tools/htmlify/to_xml_example/minus.gif
rename : docs/htmlify/to_xml_example/output.xml => tools/htmlify/to_xml_example/output.xml
rename : docs/htmlify/to_xml_example/plus.gif => tools/htmlify/to_xml_example/plus.gif
rename : docs/htmlify/to_xml_example/stylesheet.xsl => tools/htmlify/to_xml_example/stylesheet.xsl
rename : docs/htmlify/to_xml_example/test.cpp => tools/htmlify/to_xml_example/test.cpp
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a file name given as a string in addition to taking istream objects.

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can sometimes cause B to be very slightly non-symmetric.

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default_memory_manager is way more readable and clear.

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and also that it works with the one_vs_all_trainer without issue.

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   with any kind of trainer object rather than only ones which produce
   dlib::decision_function objects.  I also made it work with trainers that only
   take std::vectors.
 - train_probabilistic_decision_function() no longer accepts column vectors of
   samples and labels.  Now it only accepts std::vectors of samples and labels.
 - Added a new generic_probabilistic_decision_function object which is returned by
   the train_probabilistic_decision_function().  The old probabilistic_decision_function
   still exists and can be constructed from a generic_probabilistic_decision_function.
   This way backwards compatibility is maintained with older code so long as that
   code used std::vectors to hold samples and labels.

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