Add -R option to matlab and python interface

diff --git a/matlab/Makefile b/matlab/Makefile
index 67827f932b274309ece4b074727ff019ef30450f..1d41cf98b9c3374fdceb2214d743134f614aff0d 100644 (file)
--- a/matlab/Makefile
+++ b/matlab/Makefile
@@ -20,14 +20,14 @@ octave:
        @echo "please type make under Octave"
 binary: train.$(MEX_EXT) predict.$(MEX_EXT) libsvmread.$(MEX_EXT) libsvmwrite.$(MEX_EXT)
 
-train.$(MEX_EXT): train.c ../linear.h ../tron.cpp ../linear.cpp linear_model_matlab.c \
+train.$(MEX_EXT): train.c ../linear.h ../newton.cpp ../linear.cpp linear_model_matlab.c \
                ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
-       $(MEX) $(MEX_OPTION) train.c ../tron.cpp ../linear.cpp linear_model_matlab.c \
+       $(MEX) $(MEX_OPTION) train.c ../newton.cpp ../linear.cpp linear_model_matlab.c \
                ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
 
-predict.$(MEX_EXT): predict.c ../linear.h ../tron.cpp ../linear.cpp linear_model_matlab.c \
+predict.$(MEX_EXT): predict.c ../linear.h ../newton.cpp ../linear.cpp linear_model_matlab.c \
                ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
-       $(MEX) $(MEX_OPTION) predict.c ../tron.cpp ../linear.cpp linear_model_matlab.c \
+       $(MEX) $(MEX_OPTION) predict.c ../newton.cpp ../linear.cpp linear_model_matlab.c \
                ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
 
 libsvmread.$(MEX_EXT): libsvmread.c

diff --git a/matlab/make.m b/matlab/make.m
index 9cb8d70717b4b026cfa0b06eb88f90c9dc508a97..599bb76e08ccdcad070a1fb6761b95e38b7fc132 100644 (file)
--- a/matlab/make.m
+++ b/matlab/make.m
@@ -5,15 +5,15 @@ try
        if(exist('OCTAVE_VERSION', 'builtin'))
                mex libsvmread.c
                mex libsvmwrite.c
-               mex -I.. train.c linear_model_matlab.c ../linear.cpp ../tron.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
-               mex -I.. predict.c linear_model_matlab.c ../linear.cpp ../tron.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
+               mex -I.. train.c linear_model_matlab.c ../linear.cpp ../newton.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
+               mex -I.. predict.c linear_model_matlab.c ../linear.cpp ../newton.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
        % This part is for MATLAB
        % Add -largeArrayDims on 64-bit machines of MATLAB
        else
                mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims libsvmread.c
                mex CFLAGS="\$CFLAGS -std=c99" -largeArrayDims libsvmwrite.c
-               mex CFLAGS="\$CFLAGS -std=c99" -I.. -largeArrayDims train.c linear_model_matlab.c ../linear.cpp ../tron.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
-               mex CFLAGS="\$CFLAGS -std=c99" -I.. -largeArrayDims predict.c linear_model_matlab.c ../linear.cpp ../tron.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
+               mex CFLAGS="\$CFLAGS -std=c99" -I.. -largeArrayDims train.c linear_model_matlab.c ../linear.cpp ../newton.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
+               mex CFLAGS="\$CFLAGS -std=c99" -I.. -largeArrayDims predict.c linear_model_matlab.c ../linear.cpp ../newton.cpp ../blas/daxpy.c ../blas/ddot.c ../blas/dnrm2.c ../blas/dscal.c
        end
 catch err
        fprintf('Error: %s failed (line %d)\n', err.stack(1).file, err.stack(1).line);

diff --git a/matlab/train.c b/matlab/train.c
index 63cd4b60f5ee09b2bc439186ed491eb4297687f8..498772a5dab2ef31aadc9eb075fe14d44b575a19 100644 (file)
--- a/matlab/train.c
+++ b/matlab/train.c
@@ -58,6 +58,8 @@ void exit_with_help()
        "               |f'(alpha)|_1 <= eps |f'(alpha0)|,\n"
        "               where f is the dual function (default 0.1)\n"
        "-B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default -1)\n"
+       "-R : not regularize the bias; must with -B 1 to have the bias; DON'T use this unless you know what it is\n"
+       "       (for -s 0, 2, 5, 6, 11)\n"
        "-wi weight: weights adjust the parameter C of different classes (see README for details)\n"
        "-v n: n-fold cross validation mode\n"
        "-C : find parameters (C for -s 0, 2 and C, p for -s 11)\n"
@@ -166,6 +168,7 @@ int parse_command_line(int nrhs, const mxArray *prhs[], char *model_file_name)
        param.weight_label = NULL;
        param.weight = NULL;
        param.init_sol = NULL;
+       param.regularize_bias = 1;
        flag_cross_validation = 0;
        col_format_flag = 0;
        flag_C_specified = 0;
@@ -199,7 +202,8 @@ int parse_command_line(int nrhs, const mxArray *prhs[], char *model_file_name)
        {
                if(argv[i][0] != '-') break;
                ++i;
-               if(i>=argc && argv[i-1][1] != 'q' && argv[i-1][1] != 'C') // since options -q and -C have no parameter
+               if(i>=argc && argv[i-1][1] != 'q' && argv[i-1][1] != 'C'
+                               && argv[i-1][1] != 'R') // since options -q and -C have no parameter
                        return 1;
                switch(argv[i-1][1])
                {
@@ -248,6 +252,10 @@ int parse_command_line(int nrhs, const mxArray *prhs[], char *model_file_name)
                                flag_find_parameters = 1;
                                i--;
                                break;
+                       case 'R':
+                               param.regularize_bias = 0;
+                               i--;
+                               break;
                        default:
                                mexPrintf("unknown option\n");
                                return 1;

diff --git a/python/liblinear.py b/python/liblinear.py
index ae2bd770994a8ec91b1d99abe2578b53a661c0ca..64e21bb8c2d52ee5a3d1a1b363b9d15eedde13cc 100644 (file)
--- a/python/liblinear.py
+++ b/python/liblinear.py
@@ -228,8 +228,8 @@ class problem(Structure):
 
 
 class parameter(Structure):
-       _names = ["solver_type", "eps", "C", "nr_weight", "weight_label", "weight", "p", "nu", "init_sol"]
-       _types = [c_int, c_double, c_double, c_int, POINTER(c_int), POINTER(c_double), c_double, c_double, POINTER(c_double)]
+       _names = ["solver_type", "eps", "C", "nr_weight", "weight_label", "weight", "p", "nu", "init_sol", "regularize_bias"]
+       _types = [c_int, c_double, c_double, c_int, POINTER(c_int), POINTER(c_double), c_double, c_double, POINTER(c_double), c_int]
        _fields_ = genFields(_names, _types)
 
        def __init__(self, options = None):
@@ -258,6 +258,7 @@ class parameter(Structure):
                self.weight = None
                self.init_sol = None
                self.bias = -1
+               self.regularize_bias = 1
                self.flag_cross_validation = False
                self.flag_C_specified = False
                self.flag_p_specified = False
@@ -316,7 +317,8 @@ class parameter(Structure):
                                self.print_func = PRINT_STRING_FUN(print_null)
                        elif argv[i] == "-C":
                                self.flag_find_parameters = True
-
+                       elif argv[i] == "-R":
+                               self.regularize_bias = 0
                        else:
                                raise ValueError("Wrong options")
                        i += 1

diff --git a/python/liblinearutil.py b/python/liblinearutil.py
index 9427974501f26f82e0352e37270e62317ac5da97..ce24bcfb9a21a5d4cc590125b7e8ffa3b0957799 100644 (file)
--- a/python/liblinearutil.py
+++ b/python/liblinearutil.py
@@ -94,6 +94,8 @@ def train(arg1, arg2=None, arg3=None):
                                |f'(alpha)|_1 <= eps |f'(alpha0)|,
                                where f is the dual function (default 0.1)
                -B bias : if bias >= 0, instance x becomes [x; bias]; if < 0, no bias term added (default -1)
+               -R : not regularize the bias; must with -B 1 to have the bias; DON'T use this unless you know what it is
+                       (for -s 0, 2, 5, 6, 11)"
                -wi weight: weights adjust the parameter C of different classes (see README for details)
                -v n: n-fold cross validation mode
                -C : find parameters (C for -s 0, 2 and C, p for -s 11)