Merge branch 'clean-docs' of git://github.com/shelhamer/shogun

shogun-toolbox · Mar 25, 2012 · f8c2851 · f8c2851
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diff --git a/doc/pages/DeveloperTutorial.mainpage b/doc/pages/DeveloperTutorial.mainpage
@@ -108,7 +108,8 @@ CSimpleKernel<float64_t> (for strings it would be CStringKernel, for sparse
 features CSparseKernel).
 
 Essentially we only need to overload the CKernel::compute() function with our
-own implementation of compute. All the rest gets empty defaults. An example for our compute() function could be
+own implementation of compute. All the rest gets empty defaults. An example for
+our compute() function could be
 
 
 \verbatim
@@ -117,7 +118,7 @@ virtual float64_t compute(int32_t idx_a, int32_t idx_b)
     int32_t alen, blen;
     bool afree, bfree;
 
-    float64_t* avec= 
+    float64_t* avec=
         ((CSimpleFeatures<float64_t>*) lhs)->get_feature_vector(idx_a, alen, afree);
     float64_t* bvec=
         ((CSimpleFeatures<float64_t>*) rhs)->get_feature_vector(idx_b, blen, bfree);
@@ -183,11 +184,11 @@ and finally tell swig to wrap all functions found in the header
 \endverbatim
 
 In case you got your object working we will happily integrate it into shogun
-provided you follow a number of basic coding conventions detailed in \subpage devel (see
-FORMATTING for formatting instructions, MACROS on how to use and name macros,
-TYPES on which types to use, FUNCTIONS on how functions should look like and
-NAMING CONVENTIONS for the naming scheme. Note that in case you change the API
-in a way that breaks ABI compatibility you need to increase the major number of
-the libshogun soname (see \subpage soname ).
+provided you follow a number of basic coding conventions detailed in \subpage
+devel (see FORMATTING for formatting instructions, MACROS on how to use and name
+macros, TYPES on which types to use, FUNCTIONS on how functions should look like
+and NAMING CONVENTIONS for the naming scheme. Note that in case you change the
+API in a way that breaks ABI compatibility you need to increase the major number
+of the libshogun soname (see \subpage soname ).
 
 */
diff --git a/doc/pages/Documentation.mainpage b/doc/pages/Documentation.mainpage
@@ -25,7 +25,7 @@
   Perceptrons and features algorithms to train hidden markov models. The input
   feature-objects can be dense, sparse or strings and of type
   int/short/double/char and can be converted into different feature types.
-  Chains of preprocessors (e.g.  substracting the mean) can be attached to each
+  Chains of preprocessors (e.g.  subtracting the mean) can be attached to each
   feature object allowing for on-the-fly pre-processing.
 
   SHOGUN is implemented in C++ and interfaces to Matlab(tm), R, Octave and

diff --git a/doc/pages/EierlegendeWollmilchSauInterface.mainpage b/doc/pages/EierlegendeWollmilchSauInterface.mainpage
@@ -2,9 +2,9 @@
 
 As mentioned before SHOGUN interfaces to several programming languages and
 toolkits such as Matlab(tm), R, Python, Octave. The special
-Eierlegendewollmilchsau (elwms) interface does everything in one file. It is
-a chimera of all the \subpage staticinterfaces, thus all the examples and documentation
-form \subpage staticinterfaces still apply.
+Eierlegendewollmilchsau (elwms) interface does everything in one file. It is a
+chimera of all the \subpage staticinterfaces, thus all the examples and
+documentation form \subpage staticinterfaces still apply.
 
 One of the key strengths of this interface is that it provides the
 \verbatim
@@ -13,7 +13,8 @@ elwms('run_r', 'A', A, ..., 'rfile', '...')
 elwms('run_octave', 'A', A, ..., octavecode, '...')
 \endverbatim
 
-interoperability commands that enable running of code in foreign languages. For example 
+interoperability commands that enable running of code in foreign languages. For
+example
 
 \verbinclude octave_matplotlib.m
 

diff --git a/doc/pages/ExamplesLibshogun.mainpage b/doc/pages/ExamplesLibshogun.mainpage
@@ -2,28 +2,29 @@
 
 This page lists ready to run shogun examples for the C++ libshogun interface.
 
-\li \subpage libshogun_base_examples 
-\li \subpage libshogun_basic_examples 
-\li \subpage libshogun_classifier_examples 
-\li \subpage libshogun_clustering_examples 
-\li \subpage libshogun_converter_examples 
-\li \subpage libshogun_features_examples 
-\li \subpage libshogun_kernel_examples 
-\li \subpage libshogun_library_examples 
-\li \subpage libshogun_mathematics_examples 
-\li \subpage libshogun_modelselection_examples 
-\li \subpage libshogun_parameter_examples 
-\li \subpage libshogun_preprocessor_examples 
-\li \subpage libshogun_serialization_examples 
-\li \subpage libshogun_splitting_examples 
-\li \subpage libshogun_streaming_examples 
+\li \subpage libshogun_base_examples
+\li \subpage libshogun_basic_examples
+\li \subpage libshogun_classifier_examples
+\li \subpage libshogun_clustering_examples
+\li \subpage libshogun_converter_examples
+\li \subpage libshogun_features_examples
+\li \subpage libshogun_kernel_examples
+\li \subpage libshogun_library_examples
+\li \subpage libshogun_mathematics_examples
+\li \subpage libshogun_modelselection_examples
+\li \subpage libshogun_parameter_examples
+\li \subpage libshogun_preprocessor_examples
+\li \subpage libshogun_serialization_examples
+\li \subpage libshogun_splitting_examples
+\li \subpage libshogun_streaming_examples
 
 To run the examples you will need to manually compile them via
 \verbatim
 g++ name_of_example.cpp -lshogun
 \endverbatim
 
-in case you installed libshogun to a nonstandard directory you will need to specify the appropriate library and include paths, e.g.
+in case you installed libshogun to a nonstandard directory you will need to
+specify the appropriate library and include paths, e.g.
 \verbatim
 g++ -I/path/to/libshogun/includes name_of_example.cpp -L/path/to/libshogun/sofile -lshogun
 \endverbatim
@@ -32,11 +33,12 @@ Then the examples are standard binary executables and can be started via
 \verbatim
 ./name_of_example
 \endverbatim
-respectively if the libraries are in nonstandard locations (such that they cannot be found by the dynamic linker)
+respectively if the libraries are in nonstandard locations (such that they
+cannot be found by the dynamic linker)
 \verbatim
 LD_LIBRARY_PATH=path/to/libshogun ./name_of_example
 \endverbatim
-		
+
 \section libshogun_base_examples Base
 
 

diff --git a/doc/pages/ExamplesStaticOctave.mainpage b/doc/pages/ExamplesStaticOctave.mainpage
@@ -1,18 +1,19 @@
 /*! \page octave_static_examples Examples for Static Matlab(tm) and Octave Interface
 
-This page lists ready to run shogun examples for the Static Matlab(tm) and Octave interface.
-
-\li \subpage octave_static_classifier_examples 
-\li \subpage octave_static_clustering_examples 
-\li \subpage octave_static_distance_examples 
-\li \subpage octave_static_distribution_examples 
-\li \subpage octave_static_features_examples 
-\li \subpage octave_static_kernel_examples 
-\li \subpage octave_static_misc_examples 
-\li \subpage octave_static_mkl_examples 
-\li \subpage octave_static_preproc_examples 
-\li \subpage octave_static_regression_examples 
-\li \subpage octave_static_structure_examples 
+This page lists ready to run shogun examples for the Static Matlab(tm) and
+Octave interface.
+
+\li \subpage octave_static_classifier_examples
+\li \subpage octave_static_clustering_examples
+\li \subpage octave_static_distance_examples
+\li \subpage octave_static_distribution_examples
+\li \subpage octave_static_features_examples
+\li \subpage octave_static_kernel_examples
+\li \subpage octave_static_misc_examples
+\li \subpage octave_static_mkl_examples
+\li \subpage octave_static_preproc_examples
+\li \subpage octave_static_regression_examples
+\li \subpage octave_static_structure_examples
 
 To run the examples issue
 \verbatim
@@ -24,8 +25,9 @@ or start up matlab or octave and then type
 name_of_example
 \endverbatim
 
-Note that you have to make sure that the sg.oct or sg.mexglx (name varies with architecture)
-has to be in the matlab/octave path. This can be achieved using the addpath command:
+Note that you have to make sure that the sg.oct or sg.mexglx (name varies with
+architecture) has to be in the matlab/octave path. This can be achieved using
+the addpath command:
 \verbatim
 addpath /path/to/octave
 \endverbatim
@@ -34,13 +36,15 @@ respectively
 addpath /path/to/matlab
 \endverbatim
 
-Finally note that for non-root installations you will have to make sure that libshogun and libshogun ui can be found by the dynamic linker, e.g. you will need to set:
+Finally note that for non-root installations you will have to make sure that
+libshogun and libshogun ui can be found by the dynamic linker, e.g. you will
+need to set:
 
 \verbatim
 LD_LIBRARY_PATH=path/to/libshogun:path/to/libshogunui
 \endverbatim
 before starting matlab.
-		
+
 \section octave_static_classifier_examples Classifier
 
 

diff --git a/doc/pages/FAQ.mainpage b/doc/pages/FAQ.mainpage
@@ -2,16 +2,16 @@
 \page faq Frequently Asked Questions
 
 \li Q: I am puzzled, shogun interfaces to so many languages but which language
-and shogun interface should I use?
-A: That depends a lot on your taste. I personally consider the modular
-interfaces (python_modular, octave_modular) to be "best". Here best means very
-flexible and easily extensible. However, in case you just want to train a single
-SVM with a single or multiple kernels all of the static interfaces are
-sufficient. And well, of course you should be using \b python http://www.python.org :-)
+and shogun interface should I use? A: That depends a lot on your taste. I
+personally consider the modular interfaces (python_modular, octave_modular) to
+be "best". Here best means very flexible and easily extensible. However, in case
+you just want to train a single SVM with a single or multiple kernels all of the
+static interfaces are sufficient. And well, of course you should be using \b
+python http://www.python.org :-)
 
-\li Q: I've found a bug, where should I report it?
-A: Either report it in our bug tracker http://trac.tuebingen.mpg.de/shogun or
-ask on the mailinglist.
+\li Q: I've found a bug, where should I report it? A: Either report it in our
+bug tracker https://github.com/shogun-toolbox/shogun/issues or ask on the
+mailinglist.
 
 \li Q:Do I need CPLEX to use multiple kernel learning?
 A: No, as of version 0.7.0 you won't need cplex if you want to learn the weights
@@ -21,11 +21,11 @@ multiple kernel learning (MKL) the GNU Linear Programming Kit (GLPK) version at
 least 4.29 or CPLEX is required. For general p-norm MKL with p>1 it will work
 nonetheless.
 
-\li Q: Is it multiple kernel learning when I use many kernels?
-A: No, a plain combination of features/kernels will remain a plain
-concatenation. Only in case you learn the kernel weights you really do MKL. In
-the static interfaces you can issue \verbatim [W]=sg('get_subkernel_weights') \endverbatim
-and check whether all weights W are still 1.0.
+\li Q: Is it multiple kernel learning when I use many kernels? A: No, a plain
+combination of features/kernels will remain a plain concatenation. Only in case
+you learn the kernel weights you really do MKL. In the static interfaces you can
+issue \verbatim [W]=sg('get_subkernel_weights') \endverbatim and check whether
+all weights W are still 1.0.
 
 \li Q:Does shogun compile under windows?
 A: Yes! With cygwin 1.7.1 the cmdline, python, python_modular and octave
@@ -42,12 +42,12 @@ to install (etc.). A plain ./configure;make;make install will fail since
 repeated slashes (e.g., '//usr/local') in cygwin are problematic but in posix
 systems simply ignored.
 
-\li Q:How does shogun do its memory management?
-A: As does python, we use reference counting internally, i.e. objects holding a
-reference to another object should increase the reference count of the object
-they are referencing and decrease the counter when they finished using the
-object. It should be noted that loops (e.g., object A holding a reference to object B
-and vice versa) are not detecting and may thus create memory leaks. However,
-this scenario can so far be easily avoided - just don't create a combined
-kernel that contains itself as a subkernel ;-)
+\li Q:How does shogun do its memory management? A: As does python, we use
+reference counting internally, i.e. objects holding a reference to another
+object should increase the reference count of the object they are referencing
+and decrease the counter when they finished using the object. It should be noted
+that loops (e.g., object A holding a reference to object B and vice versa) are
+not detecting and may thus create memory leaks. However, this scenario can so
+far be easily avoided - just don't create a combined kernel that contains itself
+as a subkernel ;-)
 */
diff --git a/doc/pages/Installation.mainpage b/doc/pages/Installation.mainpage
@@ -139,7 +139,7 @@ will autodetect and configure for the available interfaces.
 
 Call
 \verbatim./configure --help \endverbatim
-to see the list of additional options detailled below.
+to see the list of additional options detailed below.
 \verbinclude Configure.generated
 
 If this does not work for you, consult the INSTALL file for platform specific

diff --git a/doc/pages/Methods.mainpage b/doc/pages/Methods.mainpage
@@ -8,11 +8,11 @@
   ML related Algorithms/Classes/Methods implemented within shogun.
 
   \section featrep_sec Feature Representations
-  Shogun supports a wide range of feature representations. Among them are the so called
-  simple features (cf., CSimpleFeatures) that are standard 2-d Matrices, strings
-  (cf., CStringFeatures) that however in contrast to other meanings of string are
-  just a list of vectors of arbitrary length and sparse features (cf.,
-  CSparseFeatures) to efficiently represent sparse matrices.
+  Shogun supports a wide range of feature representations. Among them are the so
+  called simple features (cf., CSimpleFeatures) that are standard 2-d Matrices,
+  strings (cf., CStringFeatures) that however in contrast to other meanings of
+  string are just a list of vectors of arbitrary length and sparse features
+  (cf., CSparseFeatures) to efficiently represent sparse matrices.
 
   Each of these feature objects
 
@@ -37,9 +37,9 @@
   Many other feature types available. Some of them are based on the three basic
   feature types above, like CTOPFeatures (TOP Kernel features from CHMM),
   CFKFeatures (Fisher Kernel features from CHMM) and CRealFileFeatures (vectors
-  fetched from a binary file). It should be noted that all 
-  feature objects are derived from CFeatures 
-  More complex 
+  fetched from a binary file). It should be noted that all
+  feature objects are derived from CFeatures
+  More complex
   \li CAttributeFeatures - Features of attribute value pairs.
   \li CCombinedDotFeatures -  Features that allow stacking of dot features.
   \li CCombinedFeatures - Features that allow stacking of arbitrary features.
@@ -49,7 +49,8 @@
   \li CImplicitWeightedSpecFeatures - DotFeatures that implicitly implement weighted spectrum kernel features.
   \li CWDFeatures - DotFeatures that implicitly implement weighted degree kernel features.
 
-  In addition, labels are represented in CLabels and the alphabet of a string in CAlphabet.
+  In addition, labels are represented in CLabels and the alphabet of a string in
+  CAlphabet.
 
 
 
@@ -112,7 +113,7 @@
   \subsection other_regress Others
   \li CKRR - Kernel Ridge Regression
 
-  
+
 
   \section distrib_sec Distributions
   \li CHMM - Hidden Markov Models
@@ -142,7 +143,7 @@
   \li CAUCKernel - To maximize AUC in SVM training (takes a kernel as input)
   \li CChi2Kernel - Chi^2 Kernel
   \li CCombinedKernel - Combined kernel to work with multiple kernels
-  \li CCommUlongStringKernel - Spectrum Kernel with spectrums of up to 64bit 
+  \li CCommUlongStringKernel - Spectrum Kernel with spectrums of up to 64bit
   \li CCommWordStringKernel - Spectrum kernel with spectrum of up to 16 bit
   \li CConstKernel - A ``kernel'' returning a constant
   \li CCustomKernel - A user supplied custom kernel