add svmlight source code

thirdparty/svmlight/CMakeLists.txt

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+set (svm_learn_SRC
+    kernel.h
+    svm_common.c
+    svm_common.h
+    svm_hideo.c
+    svm_learn.c
+    svm_learn.h
+    svm_learn_main.c)
+
+add_executable (svm_learn
+    ${svm_learn_SRC})
+
+set_target_properties (svm_learn 
+    PROPERTIES 
+    RUNTIME_OUTPUT_DIRECTORY  ${TOOLS_DIR}/train/)
+
+target_link_libraries (svm_learn m)

thirdparty/svmlight/LICENSE.txt

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+SVM-Light
+---------
+
+Available at http://svmlight.joachims.org/
+
+Author: Thorsten Joachims
+	[email protected]
+
+	Cornell University
+	Department of Computer Science
+	4153 Upson Hall
+	Ithaca, NY 14853
+	USA
+
+LICENSING TERMS 
+
+This program is granted free of charge for research and education
+purposes. However you must obtain a license from the author to use it
+for commercial purposes.
+
+Scientific results produced using the software provided shall
+acknowledge the use of SVM-Light. Please cite as  
+
+       T. Joachims, Making large-Scale SVM Learning
+       Practical. Advances in Kernel Methods - Support Vector
+       Learning, B. Sch�lkopf and C. Burges and A. Smola (ed.),
+       MIT-Press, 1999. 
+       http://www-ai.cs.uni-dortmund.de/DOKUMENTE/joachims_99a.pdf
+
+Moreover shall the author of SVM-Light be informed about the
+publication.
+
+The software must not be modified and distributed without prior
+permission of the author.
+
+By using SVM-Light you agree to the licensing terms.
+
+
+NO WARRANTY 
+
+BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
+FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT
+WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER
+PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND,
+EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE
+PROGRAM IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME
+THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
+REDISTRIBUTE THE PROGRAM, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF
+THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO
+LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
+YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY
+OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED
+OF THE POSSIBILITY OF SUCH DAMAGES.

thirdparty/svmlight/Makefile

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+#
+# makefile for svm_light 
+#
+# Thorsten Joachims, 2002
+#
+
+#Use the following to compile under unix or cygwin
+CC = gcc
+LD = gcc
+
+#Uncomment the following line to make CYGWIN produce stand-alone Windows executables
+#SFLAGS= -mno-cygwin
+
+CFLAGS=  $(SFLAGS) -O3                     # release C-Compiler flags
+LFLAGS=  $(SFLAGS) -O3                     # release linker flags
+#CFLAGS= $(SFLAGS) -pg -Wall -pedantic      # debugging C-Compiler flags
+#LFLAGS= $(SFLAGS) -pg                      # debugging linker flags
+LIBS=-L. -lm                               # used libraries
+
+all: svm_learn_hideo svm_classify
+
+tidy: 
+	rm -f *.o 
+	rm -f pr_loqo/*.o
+
+clean:	tidy
+	rm -f svm_learn
+	rm -f svm_classify
+	rm -f libsvmlight.so
+
+help:   info
+
+info:
+	@echo
+	@echo "make for SVM-light               Thorsten Joachims, 1998"
+	@echo
+	@echo "Thanks to Ralf Herbrich for the initial version."
+	@echo 
+	@echo "USAGE: make [svm_learn | svm_learn_loqo | svm_learn_hideo | "
+	@echo "             libsvmlight_hideo | libsvmlight_loqo | "
+	@echo "             svm_classify | all | clean | tidy]"
+	@echo 
+	@echo "    svm_learn           builds the learning module (prefers HIDEO)"
+	@echo "    svm_learn_hideo     builds the learning module using HIDEO optimizer"
+	@echo "    svm_learn_loqo      builds the learning module using PR_LOQO optimizer"
+	@echo "    svm_classify        builds the classfication module"
+	@echo "    libsvmlight_hideo   builds shared object library that can be linked into"
+	@echo "                        other code using HIDEO"
+	@echo "    libsvmlight_loqo    builds shared object library that can be linked into"
+	@echo "                        other code using PR_LOQO"
+	@echo "    all (default)       builds svm_learn + svm_classify"
+	@echo "    clean               removes .o and target files"
+	@echo "    tidy                removes .o files"
+	@echo
+
+# Create executables svm_learn and svm_classify
+
+svm_learn_hideo: svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o 
+	$(LD) $(LFLAGS) svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o -o svm_learn $(LIBS)
+
+#svm_learn_loqo: svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o loqo
+#	$(LD) $(LFLAGS) svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o pr_loqo/pr_loqo.o -o svm_learn $(LIBS)
+
+svm_classify: svm_classify.o svm_common.o 
+	$(LD) $(LFLAGS) svm_classify.o svm_common.o -o svm_classify $(LIBS)
+
+
+# Create library libsvmlight.so, so that external code can get access to the
+# learning and classification functions of svm-light by linking this library.
+
+svm_learn_hideo_noexe: svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o 
+
+libsvmlight_hideo: svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o 
+	$(LD) -shared svm_learn.o svm_common.o svm_hideo.o -o libsvmlight.so
+
+#svm_learn_loqo_noexe: svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o loqo
+
+#libsvmlight_loqo: svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o 
+#	$(LD) -shared svm_learn.o svm_common.o svm_loqo.o  pr_loqo/pr_loqo.o -o libsvmlight.so
+
+# Compile components
+
+svm_hideo.o: svm_hideo.c
+	$(CC) -c $(CFLAGS) svm_hideo.c -o svm_hideo.o 
+
+#svm_loqo.o: svm_loqo.c 
+#	$(CC) -c $(CFLAGS) svm_loqo.c -o svm_loqo.o 
+
+svm_common.o: svm_common.c svm_common.h kernel.h
+	$(CC) -c $(CFLAGS) svm_common.c -o svm_common.o 
+
+svm_learn.o: svm_learn.c svm_common.h
+	$(CC) -c $(CFLAGS) svm_learn.c -o svm_learn.o 
+
+svm_learn_main.o: svm_learn_main.c svm_learn.h svm_common.h
+	$(CC) -c $(CFLAGS) svm_learn_main.c -o svm_learn_main.o 
+
+svm_classify.o: svm_classify.c svm_common.h kernel.h
+	$(CC) -c $(CFLAGS) svm_classify.c -o svm_classify.o
+
+#loqo: pr_loqo/pr_loqo.o
+
+#pr_loqo/pr_loqo.o: pr_loqo/pr_loqo.c
+#	$(CC) -c $(CFLAGS) pr_loqo/pr_loqo.c -o pr_loqo/pr_loqo.o
+

thirdparty/svmlight/kernel.h

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+/************************************************************************/
+/*                                                                      */
+/*   kernel.h                                                           */
+/*                                                                      */
+/*   User defined kernel function. Feel free to plug in your own.       */
+/*                                                                      */
+/*   Copyright: Thorsten Joachims                                       */
+/*   Date: 16.12.97                                                     */
+/*                                                                      */
+/************************************************************************/
+
+/* KERNEL_PARM is defined in svm_common.h The field 'custom' is reserved for */
+/* parameters of the user defined kernel. You can also access and use */
+/* the parameters of the other kernels. Just replace the line 
+             return((double)(1.0)); 
+   with your own kernel. */
+
+  /* Example: The following computes the polynomial kernel. sprod_ss
+              computes the inner product between two sparse vectors. 
+
+      return((CFLOAT)pow(kernel_parm->coef_lin*sprod_ss(a->words,b->words)
+             +kernel_parm->coef_const,(double)kernel_parm->poly_degree)); 
+  */
+
+/* If you are implementing a kernel that is not based on a
+   feature/value representation, you might want to make use of the
+   field "userdefined" in SVECTOR. By default, this field will contain
+   whatever string you put behind a # sign in the example file. So, if
+   a line in your training file looks like
+
+   -1 1:3 5:6 #abcdefg
+
+   then the SVECTOR field "words" will contain the vector 1:3 5:6, and
+   "userdefined" will contain the string "abcdefg". */
+
+double custom_kernel(KERNEL_PARM *kernel_parm, SVECTOR *a, SVECTOR *b) 
+     /* plug in you favorite kernel */                          
+{
+  return((double)(1.0)); 
+}