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MultiClass -> Multiclass replacement in all remaining examples
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Soeren Sonnenburg committed Apr 20, 2012
1 parent ac7a60e commit fa27ebf
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Showing 16 changed files with 28 additions and 28 deletions.
4 changes: 2 additions & 2 deletions examples/undocumented/cmdline_static/classifier_libsvmmulticlass.sg
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@@ -1,5 +1,5 @@
% LibSVM MultiClass
print LibSVMMultiClass
% LibSVM Multiclass
print LibSVMMulticlass

set_kernel GAUSSIAN REAL 10 1.2
set_features TRAIN ../data/fm_train_real.dat
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4 changes: 2 additions & 2 deletions examples/undocumented/cmdline_static/mkl_multiclass.sg
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@@ -1,5 +1,5 @@
% MKL_MultiClass
print MKL_MultiClass
% MKL_Multiclass
print MKL_Multiclass


set_labels TRAIN ../data/label_train_multiclass.dat
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2 changes: 1 addition & 1 deletion examples/undocumented/csharp_modular/classifier_libsvmmulticlass_modular.cs
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Expand Up @@ -21,7 +21,7 @@ public class classifier_libsvmmulticlass_modular {

Labels labels = new Labels(trainlab);

LibSVMMultiClass svm = new LibSVMMultiClass(C, kernel, labels);
LibSVMMulticlass svm = new LibSVMMulticlass(C, kernel, labels);
svm.set_epsilon(epsilon);
svm.train();

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2 changes: 1 addition & 1 deletion examples/undocumented/csharp_modular/mkl_multiclass_modular.cs
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Expand Up @@ -46,7 +46,7 @@ public class mkl_multiclass_modular {

Labels labels = new Labels(trainlab);

MKLMultiClass mkl = new MKLMultiClass(C, kernel, labels);
MKLMulticlass mkl = new MKLMulticlass(C, kernel, labels);
mkl.set_epsilon(epsilon);
mkl.set_mkl_epsilon(epsilon);
mkl.set_mkl_norm(mkl_norm);
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2 changes: 1 addition & 1 deletion examples/undocumented/java_modular/classifier_libsvmmulticlass_modular.java
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Expand Up @@ -26,7 +26,7 @@ public static void main(String argv[]) {

Labels labels = new Labels(trainlab);

LibSVMMultiClass svm = new LibSVMMultiClass(C, kernel, labels);
LibSVMMulticlass svm = new LibSVMMulticlass(C, kernel, labels);
svm.set_epsilon(epsilon);
svm.train();

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2 changes: 1 addition & 1 deletion examples/undocumented/java_modular/mkl_multiclass_modular.java
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Expand Up @@ -50,7 +50,7 @@ public static void main(String argv[]) {

Labels labels = new Labels(trainlab);

MKLMultiClass mkl = new MKLMultiClass(C, kernel, labels);
MKLMulticlass mkl = new MKLMulticlass(C, kernel, labels);
mkl.set_epsilon(epsilon);
mkl.set_mkl_epsilon(epsilon);
mkl.set_mkl_norm(mkl_norm);
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4 changes: 2 additions & 2 deletions examples/undocumented/matlab_and_octave/classifier_libsvmmulticlass.m
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Expand Up @@ -11,8 +11,8 @@
fm_train_real=load_matrix('../data/fm_train_real.dat');
fm_test_real=load_matrix('../data/fm_test_real.dat');

% LibSVM MultiClass
disp('LibSVMMultiClass');
% LibSVM Multiclass
disp('LibSVMMulticlass');

sg('set_kernel', 'GAUSSIAN', 'REAL', size_cache, width);
sg('set_features', 'TRAIN', fm_train_real);
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4 changes: 2 additions & 2 deletions examples/undocumented/octave_modular/classifier_libsvmmulticlass_modular.m
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Expand Up @@ -6,7 +6,7 @@
fm_test_real=load_matrix('../data/fm_test_real.dat');

% libsvmmulticlass
disp('LibSVMMultiClass')
disp('LibSVMMulticlass')

feats_train=RealFeatures(fm_train_real);
feats_test=RealFeatures(fm_test_real);
Expand All @@ -18,7 +18,7 @@
num_threads=8;
labels=Labels(label_train_multiclass);

svm=LibSVMMultiClass(C, kernel, labels);
svm=LibSVMMulticlass(C, kernel, labels);
svm.set_epsilon(epsilon);
svm.parallel.set_num_threads(num_threads);
svm.train();
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2 changes: 1 addition & 1 deletion examples/undocumented/octave_modular/mkl_multiclass_modular.m
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Expand Up @@ -45,7 +45,7 @@

% MKL_MULTICLASS
disp('MKL_MULTICLASS')
mkl=MKLMultiClass(C, kernel, labels);
mkl=MKLMulticlass(C, kernel, labels);
mkl.set_epsilon(epsilon);
mkl.parallel.set_num_threads(num_threads);
mkl.set_mkl_epsilon(0.001);
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6 changes: 3 additions & 3 deletions examples/undocumented/python_modular/classifier_libsvmmulticlass_modular.py
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Expand Up @@ -10,15 +10,15 @@
def classifier_libsvmmulticlass_modular (fm_train_real=traindat,fm_test_real=testdat,label_train_multiclass=label_traindat,width=2.1,C=1,epsilon=1e-5):
from shogun.Features import RealFeatures, Labels
from shogun.Kernel import GaussianKernel
from shogun.Classifier import LibSVMMultiClass
from shogun.Classifier import LibSVMMulticlass

feats_train=RealFeatures(fm_train_real)
feats_test=RealFeatures(fm_test_real)
kernel=GaussianKernel(feats_train, feats_train, width)

labels=Labels(label_train_multiclass)

svm=LibSVMMultiClass(C, kernel, labels)
svm=LibSVMMulticlass(C, kernel, labels)
svm.set_epsilon(epsilon)
svm.train()

Expand All @@ -28,5 +28,5 @@ def classifier_libsvmmulticlass_modular (fm_train_real=traindat,fm_test_real=tes
return predictions, svm, predictions.get_labels()

if __name__=='__main__':
print('LibSVMMultiClass' )
print('LibSVMMulticlass' )
classifier_libsvmmulticlass_modular(*parameter_list[0])
4 changes: 2 additions & 2 deletions examples/undocumented/python_modular/mkl_multiclass_modular.py
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Expand Up @@ -13,7 +13,7 @@ def mkl_multiclass_modular(fm_train_real, fm_test_real, label_train_multiclass,

from shogun.Features import CombinedFeatures, RealFeatures, Labels
from shogun.Kernel import CombinedKernel, GaussianKernel, LinearKernel,PolyKernel
from shogun.Classifier import MKLMultiClass
from shogun.Classifier import MKLMulticlass

kernel = CombinedKernel()
feats_train = CombinedFeatures()
Expand Down Expand Up @@ -44,7 +44,7 @@ def mkl_multiclass_modular(fm_train_real, fm_test_real, label_train_multiclass,

labels = Labels(label_train_multiclass)

mkl = MKLMultiClass(C, kernel, labels)
mkl = MKLMulticlass(C, kernel, labels)

mkl.set_epsilon(epsilon);
mkl.parallel.set_num_threads(num_threads)
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2 changes: 1 addition & 1 deletion examples/undocumented/python_static/classifier_libsvmmulticlass.py
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Expand Up @@ -30,5 +30,5 @@ def classifier_libsvm_multiclass (fm_train_real=traindat,fm_test_real=testdat,
return result, kernel_matrix

if __name__=='__main__':
print('LibSVMMultiClass')
print('LibSVMMulticlass')
classifier_libsvm_multiclass(*parameter_list[0])
4 changes: 2 additions & 2 deletions examples/undocumented/r_modular/classifier_libsvmmulticlass_modular.R
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Expand Up @@ -5,7 +5,7 @@ fm_test_real <- t(as.matrix(read.table('../data/fm_test_real.dat')))
label_train_multiclass <- as.real(read.table('../data/label_train_multiclass.dat')$V1)

# libsvmmulticlass
print('LibSVMMultiClass')
print('LibSVMMulticlass')

feats_train <- RealFeatures(fm_train_real)
feats_test <- RealFeatures(fm_test_real)
Expand All @@ -17,7 +17,7 @@ epsilon <- 1e-5
num_threads <- as.integer(8)
labels <- Labels(label_train_multiclass)

svm <- LibSVMMultiClass(C, kernel, labels)
svm <- LibSVMMulticlass(C, kernel, labels)
dump <- svm$set_epsilon(svm, epsilon)
dump <- svm$parallel$set_num_threads(svm$parallel, num_threads)
dump <- svm$train(svm)
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4 changes: 2 additions & 2 deletions examples/undocumented/r_modular/classifier_mpdsvm_modular.R
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Expand Up @@ -5,7 +5,7 @@ fm_test_real <- t(as.matrix(read.table('../data/fm_test_real.dat')))
label_train_multiclass <- as.real(read.table('../data/label_train_multiclass.dat')$V1)

# libsvmmulticlass
print('LibSVMMultiClass')
print('LibSVMMulticlass')

feats_train <- RealFeatures(fm_train_real)
feats_test <- RealFeatures(fm_test_real)
Expand All @@ -17,7 +17,7 @@ epsilon <- 1e-5
num_threads <- as.integer(8)
labels <- Labels(label_train_multiclass)

svm <- LibSVMMultiClass(C, kernel, labels)
svm <- LibSVMMulticlass(C, kernel, labels)
dump <- svm$set_epsilon(svm, epsilon)
dump <- svm$parallel$set_num_threads(svm$parallel, num_threads)
dump <- svm$train(svm)
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6 changes: 3 additions & 3 deletions examples/undocumented/r_modular/mkl_multiclass_modular.R
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Expand Up @@ -4,8 +4,8 @@ fm_train_real <- t(as.matrix(read.table('../data/fm_train_real.dat')))
fm_test_real <- t(as.matrix(read.table('../data/fm_test_real.dat')))
label_train_multiclass <- as.real(as.matrix(read.table('../data/label_train_multiclass.dat')))

# MKLMultiClass
print('MKLMultiClass')
# MKLMulticlass
print('MKLMulticlass')


kernel <- CombinedKernel()
Expand Down Expand Up @@ -49,7 +49,7 @@ mkl_norm <- 1
num_threads <- as.integer(1)
labels <- Labels(label_train_multiclass)

svm <- MKLMultiClass(C, kernel, labels)
svm <- MKLMulticlass(C, kernel, labels)
dump <- svm$set_epsilon(svm, epsilon)
dump <- svm$parallel$set_num_threads(svm$parallel, num_threads)
dump <- svm$set_mkl_epsilon(svm,mkl_eps)
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4 changes: 2 additions & 2 deletions examples/undocumented/r_static/classifier_libsvmmulticlass.R
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Expand Up @@ -11,8 +11,8 @@ fm_test_real <- t(as.matrix(read.table('../data/fm_test_real.dat')))
label_train_multiclass <- as.real(as.matrix(read.table('../data/label_train_multiclass.dat')))


# LibSVM MultiClass
print('LibSVMMultiClass')
# LibSVM Multiclass
print('LibSVMMulticlass')

dump <- sg('set_features', 'TRAIN', fm_train_real)
dump <- sg('set_kernel', 'GAUSSIAN', 'REAL', size_cache, width)
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