10 files changed, 0 insertions, 670 deletions

diff --git a/data/iris/svm_light/run.sh b/data/iris/svm_light/run.sh
deleted file mode 100755
index 9040912..0000000
--- a/data/iris/svm_light/run.sh
+++ /dev/null
@@ -1,7 +0,0 @@
-#!/bin/bash
-
-
-for i in setosa virginica versicolor; do
-  ../../svm_light/svm_learn ../bezdekIris.$i-v-rest.shuf.data $i.model &>$i.learnout
-done
-
diff --git a/data/iris/svm_light/setosa.learnout b/data/iris/svm_light/setosa.learnout
deleted file mode 100644
index b5ff56e..0000000
--- a/data/iris/svm_light/setosa.learnout
+++ /dev/null
@@ -1,18 +0,0 @@
-Scanning examples...done
-Reading examples into memory...100..OK. (150 examples read)
-Setting default regularization parameter C=0.0162
-Optimizing...............done. (16 iterations)
-Optimization finished (0 misclassified, maxdiff=0.00000).
-Runtime in cpu-seconds: 0.00
-Number of SV: 36 (including 34 at upper bound)
-L1 loss: loss=5.54515
-Norm of weight vector: |w|=0.68130
-Norm of longest example vector: |x|=11.11126
-Estimated VCdim of classifier: VCdim<=30.12233
-Computing XiAlpha-estimates...done
-Runtime for XiAlpha-estimates in cpu-seconds: 0.00
-XiAlpha-estimate of the error: error<=22.67% (rho=1.00,depth=0)
-XiAlpha-estimate of the recall: recall=>66.00% (rho=1.00,depth=0)
-XiAlpha-estimate of the precision: precision=>66.00% (rho=1.00,depth=0)
-Number of kernel evaluations: 1803
-Writing model file...done
diff --git a/data/iris/svm_light/setosa.model b/data/iris/svm_light/setosa.model
deleted file mode 100644
index 139fa72..0000000
--- a/data/iris/svm_light/setosa.model
+++ /dev/null
@@ -1,47 +0,0 @@
-SVM-light Version V6.02
-0 # kernel type
-3 # kernel parameter -d 
-1 # kernel parameter -g 
-1 # kernel parameter -s 
-1 # kernel parameter -r 
-empty# kernel parameter -u 
-4 # highest feature index 
-150 # number of training documents 
-37 # number of support vectors plus 1 
--1.941408 # threshold b, each following line is a SV (starting with alpha*y)
--0.016249222750612444393647493257049 1:5.5 2:2.5 3:4 4:1.3 #
-0.016249222750612444393647493257049 1:4.9000001 2:3.0999999 3:1.5 4:0.1 #
--0.016249222750612444393647493257049 1:5.0999999 2:2.5 3:3 4:1.1 #
--0.016249222750612444393647493257049 1:4.9000001 2:2.4000001 3:3.3 4:1 #
-0.016249222750612444393647493257049 1:5.6999998 2:3.8 3:1.7 4:0.30000001 #
-0.016249222750612444393647493257049 1:4.8000002 2:3.4000001 3:1.6 4:0.2 #
--0.016249222750612444393647493257049 1:5 2:2.3 3:3.3 4:1 #
--0.016249222750612444393647493257049 1:5.6999998 2:2.5999999 3:3.5 4:1 #
-0.016249222750612444393647493257049 1:5.0999999 2:3.3 3:1.7 4:0.5 #
-0.016249222750612444393647493257049 1:4.8000002 2:3.4000001 3:1.9 4:0.2 #
--0.016249222750612444393647493257049 1:5.5999999 2:2.9000001 3:3.5999999 4:1.3 #
--0.016249222750612444393647493257049 1:5 2:2 3:3.5 4:1 #
-0.016249222750612444393647493257049 1:5.0999999 2:3.8 3:1.9 4:0.40000001 #
-0.016249222750612444393647493257049 1:5 2:3 3:1.6 4:0.2 #
--0.016249222750612444393647493257049 1:5.5 2:2.4000001 3:3.7 4:1 #
-0.016249222750612444393647493257049 1:4.5 2:2.3 3:1.3 4:0.30000001 #
--0.016249222750612444393647493257049 1:5.5 2:2.4000001 3:3.8 4:1.1 #
--0.016249222750612444393647493257049 1:5.1999998 2:2.7 3:3.9000001 4:1.4 #
-0.016249222750612444393647493257049 1:5.4000001 2:3.4000001 3:1.7 4:0.2 #
-0.016249222750612444393647493257049 1:5 2:3.5 3:1.6 4:0.60000002 #
--0.016249222750612444393647493257049 1:5.8000002 2:2.7 3:3.9000001 4:1.2 #
-0.016249222750612444393647493257049 1:4.8000002 2:3.0999999 3:1.6 4:0.2 #
--0.016249222750612444393647493257049 1:5.5999999 2:2.5 3:3.9000001 4:1.1 #
-0.016249222750612444393647493257049 1:5 2:3.4000001 3:1.6 4:0.40000001 #
--0.016249222750612444393647493257049 1:5.5999999 2:3 3:4.0999999 4:1.3 #
--0.016249222750612444393647493257049 1:5.8000002 2:2.7 3:4.0999999 4:1 #
-0.016249222750612444393647493257049 1:5.4000001 2:3.9000001 3:1.7 4:0.40000001 #
-0.016249222750612444393647493257049 1:5.4000001 2:3.4000001 3:1.5 4:0.40000001 #
--0.016249222750612444393647493257049 1:5.8000002 2:2.5999999 3:4 4:1.2 #
-0.016249222750612444393647493257049 1:4.6999998 2:3.2 3:1.6 4:0.2 #
--0.016249222750612444393647493257049 1:6.0999999 2:2.8 3:4 4:1.3 #
--0.016249222750612444393647493257049 1:5.6999998 2:3 3:4.1999998 4:1.2 #
-0.016249222750612444393647493257049 1:4.9000001 2:3.0999999 3:1.5 4:0.2 #
-0.016249222750612444393647493257049 1:4.8000002 2:3 3:1.4 4:0.30000001 #
--0.00090280526935266995625095631794466 1:5.6999998 2:2.8 3:4.0999999 4:1.3 #
-0.00090280526935266518576139738172515 1:5.0999999 2:3.4000001 3:1.5 4:0.2 #
diff --git a/data/iris/svm_light/svm_predictions b/data/iris/svm_light/svm_predictions
deleted file mode 100644
index e104970..0000000
--- a/data/iris/svm_light/svm_predictions
+++ /dev/null
@@ -1,150 +0,0 @@
--1.8138697
-1.2878911
--1.7677399
--1.9612142
--2.3182909
--1.4727351
--1.883985
--2.390952
--1.7580716
--1.4075035
--1.3961381
-1.1324131
--2.1712263
--0.82728879
-0.90683775
--1.6604951
-0.79102587
-0.98026618
--1.4763009
-1.4024211
--0.9473525
-1.0194991
--0.89066993
--2.8225765
-1.0533155
--1.7677399
--2.3651247
--1.1651284
-1.0121508
--1.9282462
--1.9809116
--0.96976753
--1.2746572
--1.2054445
-0.79433894
-1.2039277
--0.27965375
--2.2387961
-1.0856154
--1.1915605
-1.0555994
--1.6263266
--1.2375276
--2.0151344
-1.1120294
--1.8655152
--1.3856573
--1.739376
--1.7851717
--2.1716776
-1.0327151
--1.5845481
-0.80212051
-1.0436653
--1.2811569
--2.0065223
--1.2849393
-1.006933
--1.4129379
--0.96243722
--2.2656703
--1.0280661
-1.0790976
--0.63842767
-1.0860306
-1.1019639
--0.61264555
-0.85730467
--1.0933789
--1.7236774
--0.99999998
--1.6915582
--0.67015871
--2.1947245
-1.013216
--1.9547325
--1.9658001
--1.3044564
--2.3703697
--1.7211588
--0.85837002
--2.2648218
-1.0553647
-1.019481
--0.74440875
--1.3338404
--1.5992446
-1.1482922
-1.1519302
-1.130698
--1.0396661
--2.8842062
-0.87955707
--0.88017109
-1.1487436
-0.8749712
-0.84158805
--1.5333811
--0.97333327
-1.006951
--1.2981734
--2.287273
-1.0064997
--0.42758489
--1.7201116
--2.0677999
--2.4024529
-0.89317031
--1.4807336
-1.1321965
--2.0593956
--2.5532998
--1.6059789
--0.9964522
-0.92111895
--1.4496342
--1.9822027
-1.1718446
-0.95768883
-1
-1.1642435
--1.167647
--2.1102105
-1.0708647
--1.2318765
--1.621497
--2.2222218
-0.99078303
--0.9934823
-1.0461659
--2.6156338
--1.0127647
--1.4688986
--2.6475091
-0.99666888
--1.229376
-0.96728484
--2.1252771
-0.9133555
--1.3560207
--2.6238667
-1.1281974
-1.0528822
-0.9540508
--1.6983106
--0.46051667
--1.0658815
--3.2014274
--2.9727374
--2.510131
diff --git a/data/iris/svm_light/versicolor-v-rest.model b/data/iris/svm_light/versicolor-v-rest.model
deleted file mode 100644
index e2f8f03..0000000
--- a/data/iris/svm_light/versicolor-v-rest.model
+++ /dev/null
@@ -1,112 +0,0 @@
-SVM-light Version V6.02
-0 # kernel type
-3 # kernel parameter -d 
-1 # kernel parameter -g 
-1 # kernel parameter -s 
-1 # kernel parameter -r 
-empty# kernel parameter -u 
-4 # highest feature index 
-150 # number of training documents 
-102 # number of support vectors plus 1 
-0.72531938 # threshold b, each following line is a SV (starting with alpha*y)
--0.016249222750612423576965781535364 1:4.5 2:2.3 3:1.3 4:0.30000001 #
-0.016249222750612423576965781535364 1:5.5999999 2:2.9000001 3:3.5999999 4:1.3 #
--0.016249222750612423576965781535364 1:6.5 2:3 3:5.5 4:1.8 #
--0.016249222750612423576965781535364 1:7.6999998 2:2.5999999 3:6.9000001 4:2.3 #
-0.016249222750612423576965781535364 1:5.0999999 2:2.5 3:3 4:1.1 #
-0.016249222750612423576965781535364 1:4.9000001 2:2.4000001 3:3.3 4:1 #
--0.016249222750612423576965781535364 1:4.3000002 2:3 3:1.1 4:0.1 #
-0.016249222750612423576965781535364 1:6.9000001 2:3.0999999 3:4.9000001 4:1.5 #
--0.016249222750612423576965781535364 1:4.4000001 2:3 3:1.3 4:0.2 #
-0.016249222750612423576965781535364 1:7 2:3.2 3:4.6999998 4:1.4 #
--0.016249222750612423576965781535364 1:7.6999998 2:2.8 3:6.6999998 4:2 #
-0.016249222750612423576965781535364 1:5 2:2.3 3:3.3 4:1 #
--0.016249222750612423576965781535364 1:4.4000001 2:2.9000001 3:1.4 4:0.2 #
-0.016249222750612423576965781535364 1:6.6999998 2:3 3:5 4:1.7 #
--0.016249222750612423576965781535364 1:7.5999999 2:3 3:6.5999999 4:2.0999999 #
--0.016249222750612423576965781535364 1:7.6999998 2:3 3:6.0999999 4:2.3 #
-0.016249222750612423576965781535364 1:5.6999998 2:2.5999999 3:3.5 4:1 #
-0.016249222750612423576965781535364 1:5 2:2 3:3.5 4:1 #
--0.0062366315768189184431946614495246 1:4.4000001 2:3.2 3:1.3 4:0.2 #
-0.016249222750612423576965781535364 1:6.6999998 2:3.0999999 3:4.6999998 4:1.5 #
--0.016249222750612423576965781535364 1:4.9000001 2:2.5 3:4.5 4:1.7 #
-0.016249222750612423576965781535364 1:6.6999998 2:3.0999999 3:4.4000001 4:1.4 #
--0.016249222750612423576965781535364 1:6 2:2.2 3:5 4:1.5 #
-0.016249222750612423576965781535364 1:6 2:3.4000001 3:4.5 4:1.6 #
--0.016249222750612423576965781535364 1:4.8000002 2:3 3:1.4 4:0.30000001 #
-0.016249222750612423576965781535364 1:6.3000002 2:3.3 3:4.6999998 4:1.6 #
--0.016249222750612423576965781535364 1:6 2:3 3:4.8000002 4:1.8 #
-0.016249222750612423576965781535364 1:5.5 2:2.4000001 3:3.7 4:1 #
--0.016249222750612423576965781535364 1:5.6999998 2:2.5 3:5 4:2 #
--0.016249222750612423576965781535364 1:5.8000002 2:2.8 3:5.0999999 4:2.4000001 #
-0.016249222750612423576965781535364 1:6.4000001 2:3.2 3:4.5 4:1.5 #
-0.016249222750612423576965781535364 1:6.5999999 2:3 3:4.4000001 4:1.4 #
--0.016249222750612423576965781535364 1:6.0999999 2:3 3:4.9000001 4:1.8 #
--0.016249222750612423576965781535364 1:4.8000002 2:3 3:1.4 4:0.1 #
-0.016249222750612423576965781535364 1:5.9000001 2:3.2 3:4.8000002 4:1.8 #
-0.016249222750612423576965781535364 1:6 2:2.7 3:5.0999999 4:1.6 #
--0.016249222750612423576965781535364 1:7.3000002 2:2.9000001 3:6.3000002 4:1.8 #
--0.016249222750612423576965781535364 1:7.4000001 2:2.8 3:6.0999999 4:1.9 #
-0.016249222750612423576965781535364 1:5.5 2:2.4000001 3:3.8 4:1.1 #
-0.016249222750612423576965781535364 1:5.1999998 2:2.7 3:3.9000001 4:1.4 #
--0.016249222750612423576965781535364 1:4.6999998 2:3.2 3:1.6 4:0.2 #
--0.016249222750612423576965781535364 1:6.6999998 2:2.5 3:5.8000002 4:1.8 #
-0.016249222750612423576965781535364 1:6.4000001 2:2.9000001 3:4.3000002 4:1.3 #
-0.016249222750612423576965781535364 1:6.0999999 2:2.8 3:4 4:1.3 #
--0.016249222750612423576965781535364 1:6.4000001 2:3.0999999 3:5.5 4:1.8 #
-0.016249222750612423576965781535364 1:6.8000002 2:2.8 3:4.8000002 4:1.4 #
--0.016249222750612423576965781535364 1:7.0999999 2:3 3:5.9000001 4:2.0999999 #
-0.016249222750612423576965781535364 1:5.5999999 2:3 3:4.0999999 4:1.3 #
--0.016249222750612423576965781535364 1:4.5999999 2:3.0999999 3:1.5 4:0.2 #
-0.016249222750612423576965781535364 1:6.5999999 2:2.9000001 3:4.5999999 4:1.3 #
--0.016249222750612423576965781535364 1:7.1999998 2:3.2 3:6 4:1.8 #
--0.010008109004404408537425297254231 1:6.9000001 2:3.0999999 3:5.4000001 4:2.0999999 #
-0.016249222750612423576965781535364 1:5.6999998 2:3 3:4.1999998 4:1.2 #
-0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:3.9000001 4:1.2 #
--0.016249222750612423576965781535364 1:4.9000001 2:3 3:1.4 4:0.2 #
-0.016249222750612423576965781535364 1:6.5 2:2.8 3:4.5999999 4:1.5 #
--0.016249222750612423576965781535364 1:6.0999999 2:2.5999999 3:5.5999999 4:1.4 #
-0.016249222750612423576965781535364 1:5.9000001 2:3 3:4.1999998 4:1.5 #
--0.016249222750612423576965781535364 1:6.3000002 2:2.5 3:5 4:1.9 #
-0.016249222750612423576965781535364 1:5.6999998 2:2.9000001 3:4.1999998 4:1.3 #
--0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:5.0999999 4:1.9 #
-0.016249222750612423576965781535364 1:6.0999999 2:3 3:4.5999999 4:1.4 #
--0.016249222750612423576965781535364 1:5 2:3 3:1.6 4:0.2 #
-0.016249222750612423576965781535364 1:5.5999999 2:3 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:6.5 2:3 3:5.8000002 4:2.2 #
--0.016249222750612423576965781535364 1:6.4000001 2:2.8 3:5.5999999 4:2.2 #
-0.016249222750612423576965781535364 1:5.6999998 2:2.8 3:4.0999999 4:1.3 #
-0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:4.0999999 4:1 #
--0.016249222750612423576965781535364 1:4.5999999 2:3.2 3:1.4 4:0.2 #
--0.016249222750612423576965781535364 1:4.9000001 2:3.0999999 3:1.5 4:0.1 #
-0.016249222750612423576965781535364 1:6.0999999 2:2.9000001 3:4.6999998 4:1.4 #
-0.016249222750612423576965781535364 1:6 2:2.9000001 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:6.8000002 2:3 3:5.5 4:2.0999999 #
--0.016249222750612423576965781535364 1:7.1999998 2:3 3:5.8000002 4:1.6 #
-0.016249222750612423576965781535364 1:5.5999999 2:2.5 3:3.9000001 4:1.1 #
-0.016249222750612423576965781535364 1:5.8000002 2:2.5999999 3:4 4:1.2 #
--0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:5.0999999 4:1.9 #
-0.016249222750612423576965781535364 1:6.1999998 2:2.9000001 3:4.3000002 4:1.3 #
--0.016249222750612423576965781535364 1:5.5999999 2:2.8 3:4.9000001 4:2 #
-0.016249222750612423576965781535364 1:5.4000001 2:3 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:4.8000002 2:3.0999999 3:1.6 4:0.2 #
-0.016249222750612423576965781535364 1:6.0999999 2:2.8 3:4.6999998 4:1.2 #
--0.016249222750612423576965781535364 1:6.4000001 2:2.8 3:5.5999999 4:2.0999999 #
-0.016249222750612423576965781535364 1:5.5999999 2:2.7 3:4.1999998 4:1.3 #
--0.016249222750612423576965781535364 1:6.4000001 2:2.7 3:5.3000002 4:1.9 #
-0.016249222750612423576965781535364 1:5.6999998 2:2.8 3:4.5 4:1.3 #
--0.016249222750612423576965781535364 1:6.3000002 2:2.8 3:5.0999999 4:1.5 #
--0.016249222750612423576965781535364 1:6.3000002 2:2.9000001 3:5.5999999 4:1.8 #
-0.016249222750612423576965781535364 1:6.3000002 2:2.5 3:4.9000001 4:1.5 #
-0.016249222750612423576965781535364 1:5.5 2:2.5 3:4 4:1.3 #
--0.016249222750612423576965781535364 1:4.6999998 2:3.2 3:1.3 4:0.2 #
-0.016249222750612423576965781535364 1:6.3000002 2:2.3 3:4.4000001 4:1.3 #
--0.016249222750612423576965781535364 1:6.3000002 2:2.7 3:4.9000001 4:1.8 #
-0.016249222750612423576965781535364 1:5.5 2:2.5999999 3:4.4000001 4:1.2 #
--0.016249222750612423576965781535364 1:6.1999998 2:2.8 3:4.8000002 4:1.8 #
--0.016249222750612423576965781535364 1:5.9000001 2:3 3:5.0999999 4:1.8 #
-0.016249222750612423576965781535364 1:5.5 2:2.3 3:4 4:1.3 #
-0.016249222750612423576965781535364 1:6.1999998 2:2.2 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:4.9000001 2:3.0999999 3:1.5 4:0.2 #
-0.016249222750612423576965781535364 1:6 2:2.2 3:4 4:1 #
--0.016249222750612423576965781535364 1:6.5 2:3 3:5.1999998 4:2 #
diff --git a/data/iris/svm_light/versicolor.learnout b/data/iris/svm_light/versicolor.learnout
deleted file mode 100644
index f2130b5..0000000
--- a/data/iris/svm_light/versicolor.learnout
+++ /dev/null
@@ -1,18 +0,0 @@
-Scanning examples...done
-Reading examples into memory...100..OK. (150 examples read)
-Setting default regularization parameter C=0.0162
-Optimizing.........................................................................done. (74 iterations)
-Optimization finished (50 misclassified, maxdiff=0.00038).
-Runtime in cpu-seconds: 0.00
-Number of SV: 101 (including 99 at upper bound)
-L1 loss: loss=99.35495
-Norm of weight vector: |w|=0.10241
-Norm of longest example vector: |x|=11.11126
-Estimated VCdim of classifier: VCdim<=2.24751
-Computing XiAlpha-estimates...done
-Runtime for XiAlpha-estimates in cpu-seconds: 0.00
-XiAlpha-estimate of the error: error<=66.67% (rho=1.00,depth=0)
-XiAlpha-estimate of the recall: recall=>0.00% (rho=1.00,depth=0)
-XiAlpha-estimate of the precision: precision=>0.00% (rho=1.00,depth=0)
-Number of kernel evaluations: 2578
-Writing model file...done
diff --git a/data/iris/svm_light/versicolor.model b/data/iris/svm_light/versicolor.model
deleted file mode 100644
index e2f8f03..0000000
--- a/data/iris/svm_light/versicolor.model
+++ /dev/null
@@ -1,112 +0,0 @@
-SVM-light Version V6.02
-0 # kernel type
-3 # kernel parameter -d 
-1 # kernel parameter -g 
-1 # kernel parameter -s 
-1 # kernel parameter -r 
-empty# kernel parameter -u 
-4 # highest feature index 
-150 # number of training documents 
-102 # number of support vectors plus 1 
-0.72531938 # threshold b, each following line is a SV (starting with alpha*y)
--0.016249222750612423576965781535364 1:4.5 2:2.3 3:1.3 4:0.30000001 #
-0.016249222750612423576965781535364 1:5.5999999 2:2.9000001 3:3.5999999 4:1.3 #
--0.016249222750612423576965781535364 1:6.5 2:3 3:5.5 4:1.8 #
--0.016249222750612423576965781535364 1:7.6999998 2:2.5999999 3:6.9000001 4:2.3 #
-0.016249222750612423576965781535364 1:5.0999999 2:2.5 3:3 4:1.1 #
-0.016249222750612423576965781535364 1:4.9000001 2:2.4000001 3:3.3 4:1 #
--0.016249222750612423576965781535364 1:4.3000002 2:3 3:1.1 4:0.1 #
-0.016249222750612423576965781535364 1:6.9000001 2:3.0999999 3:4.9000001 4:1.5 #
--0.016249222750612423576965781535364 1:4.4000001 2:3 3:1.3 4:0.2 #
-0.016249222750612423576965781535364 1:7 2:3.2 3:4.6999998 4:1.4 #
--0.016249222750612423576965781535364 1:7.6999998 2:2.8 3:6.6999998 4:2 #
-0.016249222750612423576965781535364 1:5 2:2.3 3:3.3 4:1 #
--0.016249222750612423576965781535364 1:4.4000001 2:2.9000001 3:1.4 4:0.2 #
-0.016249222750612423576965781535364 1:6.6999998 2:3 3:5 4:1.7 #
--0.016249222750612423576965781535364 1:7.5999999 2:3 3:6.5999999 4:2.0999999 #
--0.016249222750612423576965781535364 1:7.6999998 2:3 3:6.0999999 4:2.3 #
-0.016249222750612423576965781535364 1:5.6999998 2:2.5999999 3:3.5 4:1 #
-0.016249222750612423576965781535364 1:5 2:2 3:3.5 4:1 #
--0.0062366315768189184431946614495246 1:4.4000001 2:3.2 3:1.3 4:0.2 #
-0.016249222750612423576965781535364 1:6.6999998 2:3.0999999 3:4.6999998 4:1.5 #
--0.016249222750612423576965781535364 1:4.9000001 2:2.5 3:4.5 4:1.7 #
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--0.016249222750612423576965781535364 1:6 2:2.2 3:5 4:1.5 #
-0.016249222750612423576965781535364 1:6 2:3.4000001 3:4.5 4:1.6 #
--0.016249222750612423576965781535364 1:4.8000002 2:3 3:1.4 4:0.30000001 #
-0.016249222750612423576965781535364 1:6.3000002 2:3.3 3:4.6999998 4:1.6 #
--0.016249222750612423576965781535364 1:6 2:3 3:4.8000002 4:1.8 #
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--0.016249222750612423576965781535364 1:5.6999998 2:2.5 3:5 4:2 #
--0.016249222750612423576965781535364 1:5.8000002 2:2.8 3:5.0999999 4:2.4000001 #
-0.016249222750612423576965781535364 1:6.4000001 2:3.2 3:4.5 4:1.5 #
-0.016249222750612423576965781535364 1:6.5999999 2:3 3:4.4000001 4:1.4 #
--0.016249222750612423576965781535364 1:6.0999999 2:3 3:4.9000001 4:1.8 #
--0.016249222750612423576965781535364 1:4.8000002 2:3 3:1.4 4:0.1 #
-0.016249222750612423576965781535364 1:5.9000001 2:3.2 3:4.8000002 4:1.8 #
-0.016249222750612423576965781535364 1:6 2:2.7 3:5.0999999 4:1.6 #
--0.016249222750612423576965781535364 1:7.3000002 2:2.9000001 3:6.3000002 4:1.8 #
--0.016249222750612423576965781535364 1:7.4000001 2:2.8 3:6.0999999 4:1.9 #
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-0.016249222750612423576965781535364 1:5.1999998 2:2.7 3:3.9000001 4:1.4 #
--0.016249222750612423576965781535364 1:4.6999998 2:3.2 3:1.6 4:0.2 #
--0.016249222750612423576965781535364 1:6.6999998 2:2.5 3:5.8000002 4:1.8 #
-0.016249222750612423576965781535364 1:6.4000001 2:2.9000001 3:4.3000002 4:1.3 #
-0.016249222750612423576965781535364 1:6.0999999 2:2.8 3:4 4:1.3 #
--0.016249222750612423576965781535364 1:6.4000001 2:3.0999999 3:5.5 4:1.8 #
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--0.016249222750612423576965781535364 1:7.0999999 2:3 3:5.9000001 4:2.0999999 #
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--0.016249222750612423576965781535364 1:4.5999999 2:3.0999999 3:1.5 4:0.2 #
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--0.016249222750612423576965781535364 1:7.1999998 2:3.2 3:6 4:1.8 #
--0.010008109004404408537425297254231 1:6.9000001 2:3.0999999 3:5.4000001 4:2.0999999 #
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-0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:3.9000001 4:1.2 #
--0.016249222750612423576965781535364 1:4.9000001 2:3 3:1.4 4:0.2 #
-0.016249222750612423576965781535364 1:6.5 2:2.8 3:4.5999999 4:1.5 #
--0.016249222750612423576965781535364 1:6.0999999 2:2.5999999 3:5.5999999 4:1.4 #
-0.016249222750612423576965781535364 1:5.9000001 2:3 3:4.1999998 4:1.5 #
--0.016249222750612423576965781535364 1:6.3000002 2:2.5 3:5 4:1.9 #
-0.016249222750612423576965781535364 1:5.6999998 2:2.9000001 3:4.1999998 4:1.3 #
--0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:5.0999999 4:1.9 #
-0.016249222750612423576965781535364 1:6.0999999 2:3 3:4.5999999 4:1.4 #
--0.016249222750612423576965781535364 1:5 2:3 3:1.6 4:0.2 #
-0.016249222750612423576965781535364 1:5.5999999 2:3 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:6.5 2:3 3:5.8000002 4:2.2 #
--0.016249222750612423576965781535364 1:6.4000001 2:2.8 3:5.5999999 4:2.2 #
-0.016249222750612423576965781535364 1:5.6999998 2:2.8 3:4.0999999 4:1.3 #
-0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:4.0999999 4:1 #
--0.016249222750612423576965781535364 1:4.5999999 2:3.2 3:1.4 4:0.2 #
--0.016249222750612423576965781535364 1:4.9000001 2:3.0999999 3:1.5 4:0.1 #
-0.016249222750612423576965781535364 1:6.0999999 2:2.9000001 3:4.6999998 4:1.4 #
-0.016249222750612423576965781535364 1:6 2:2.9000001 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:6.8000002 2:3 3:5.5 4:2.0999999 #
--0.016249222750612423576965781535364 1:7.1999998 2:3 3:5.8000002 4:1.6 #
-0.016249222750612423576965781535364 1:5.5999999 2:2.5 3:3.9000001 4:1.1 #
-0.016249222750612423576965781535364 1:5.8000002 2:2.5999999 3:4 4:1.2 #
--0.016249222750612423576965781535364 1:5.8000002 2:2.7 3:5.0999999 4:1.9 #
-0.016249222750612423576965781535364 1:6.1999998 2:2.9000001 3:4.3000002 4:1.3 #
--0.016249222750612423576965781535364 1:5.5999999 2:2.8 3:4.9000001 4:2 #
-0.016249222750612423576965781535364 1:5.4000001 2:3 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:4.8000002 2:3.0999999 3:1.6 4:0.2 #
-0.016249222750612423576965781535364 1:6.0999999 2:2.8 3:4.6999998 4:1.2 #
--0.016249222750612423576965781535364 1:6.4000001 2:2.8 3:5.5999999 4:2.0999999 #
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--0.016249222750612423576965781535364 1:6.4000001 2:2.7 3:5.3000002 4:1.9 #
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--0.016249222750612423576965781535364 1:6.3000002 2:2.8 3:5.0999999 4:1.5 #
--0.016249222750612423576965781535364 1:6.3000002 2:2.9000001 3:5.5999999 4:1.8 #
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--0.016249222750612423576965781535364 1:4.6999998 2:3.2 3:1.3 4:0.2 #
-0.016249222750612423576965781535364 1:6.3000002 2:2.3 3:4.4000001 4:1.3 #
--0.016249222750612423576965781535364 1:6.3000002 2:2.7 3:4.9000001 4:1.8 #
-0.016249222750612423576965781535364 1:5.5 2:2.5999999 3:4.4000001 4:1.2 #
--0.016249222750612423576965781535364 1:6.1999998 2:2.8 3:4.8000002 4:1.8 #
--0.016249222750612423576965781535364 1:5.9000001 2:3 3:5.0999999 4:1.8 #
-0.016249222750612423576965781535364 1:5.5 2:2.3 3:4 4:1.3 #
-0.016249222750612423576965781535364 1:6.1999998 2:2.2 3:4.5 4:1.5 #
--0.016249222750612423576965781535364 1:4.9000001 2:3.0999999 3:1.5 4:0.2 #
-0.016249222750612423576965781535364 1:6 2:2.2 3:4 4:1 #
--0.016249222750612423576965781535364 1:6.5 2:3 3:5.1999998 4:2 #
diff --git a/data/iris/svm_light/virginica-v-rest.shuf.data.model b/data/iris/svm_light/virginica-v-rest.shuf.data.model
deleted file mode 100644
index ce63e74..0000000
--- a/data/iris/svm_light/virginica-v-rest.shuf.data.model
+++ /dev/null
@@ -1,94 +0,0 @@
-SVM-light Version V6.02
-0 # kernel type
-3 # kernel parameter -d 
-1 # kernel parameter -g 
-1 # kernel parameter -s 
-1 # kernel parameter -r 
-empty# kernel parameter -u 
-4 # highest feature index 
-150 # number of training documents 
-84 # number of support vectors plus 1 
-5.1687631 # threshold b, each following line is a SV (starting with alpha*y)
--0.016249222750612440924200541303435 1:5.6999998 2:2.9000001 3:4.1999998 4:1.3 #
-0.016249222750612440924200541303435 1:6.6999998 2:3.3 3:5.6999998 4:2.5 #
--0.016249222750612440924200541303435 1:6.6999998 2:3 3:5 4:1.7 #
-0.016249222750612440924200541303435 1:4.9000001 2:2.5 3:4.5 4:1.7 #
--0.016249222750612440924200541303435 1:6 2:2.7 3:5.0999999 4:1.6 #
-0.016249222750612440924200541303435 1:6 2:3 3:4.8000002 4:1.8 #
--0.016249222750612440924200541303435 1:6.3000002 2:2.5 3:4.9000001 4:1.5 #
-0.016249222750612440924200541303435 1:6.1999998 2:2.8 3:4.8000002 4:1.8 #
--0.016249222750612440924200541303435 1:5.9000001 2:3.2 3:4.8000002 4:1.8 #
-0.016249222750612440924200541303435 1:6.3000002 2:2.8 3:5.0999999 4:1.5 #
--0.016249222750612440924200541303435 1:6.9000001 2:3.0999999 3:4.9000001 4:1.5 #
-0.016249222750612440924200541303435 1:6.0999999 2:3 3:4.9000001 4:1.8 #
--0.016249222750612440924200541303435 1:6.1999998 2:2.2 3:4.5 4:1.5 #
-0.016249222750612440924200541303435 1:6.3000002 2:2.7 3:4.9000001 4:1.8 #
--0.016249222750612440924200541303435 1:6.3000002 2:3.3 3:4.6999998 4:1.6 #
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--0.016249222750612440924200541303435 1:6.8000002 2:2.8 3:4.8000002 4:1.4 #
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--0.016249222750612440924200541303435 1:5.4000001 2:3 3:4.5 4:1.5 #
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--0.016249222750612440924200541303435 1:6.0999999 2:3 3:4.5999999 4:1.4 #
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--0.016249222750612440924200541303435 1:6.5999999 2:2.9000001 3:4.5999999 4:1.3 #
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--0.016249222750612440924200541303435 1:6.5999999 2:3 3:4.4000001 4:1.4 #
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--0.016249222750612440924200541303435 1:6.4000001 2:2.9000001 3:4.3000002 4:1.3 #
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--0.016249222750612440924200541303435 1:6.1999998 2:2.9000001 3:4.3000002 4:1.3 #
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--0.016249222750612440924200541303435 1:5.5999999 2:3 3:4.0999999 4:1.3 #
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--0.016249222750612440924200541303435 1:6.0999999 2:2.8 3:4 4:1.3 #
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--0.016249222750612440924200541303435 1:5.5 2:2.3 3:4 4:1.3 #
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--0.016249222750612440924200541303435 1:5.5 2:2.5 3:4 4:1.3 #
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--0.016249222750612440924200541303435 1:5.8000002 2:2.5999999 3:4 4:1.2 #
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--0.016249222750612440924200541303435 1:5.8000002 2:2.7 3:4.0999999 4:1 #
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--0.016249222750612440924200541303435 1:5.8000002 2:2.7 3:3.9000001 4:1.2 #
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--0.016249222750612440924200541303435 1:6 2:2.2 3:4 4:1 #
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--0.013385392103451521084167552544386 1:5.1999998 2:2.7 3:3.9000001 4:1.4 #
-7.3506179476545696616085479035974e-08 1:7.4000001 2:2.8 3:6.0999999 4:1.9 #
-0.013385318597272516383256402150437 1:6.3000002 2:3.3 3:6 4:2.5 #
diff --git a/data/iris/svm_light/virginica.learnout b/data/iris/svm_light/virginica.learnout
deleted file mode 100644
index 2dee3bc..0000000
--- a/data/iris/svm_light/virginica.learnout
+++ /dev/null
@@ -1,18 +0,0 @@
-Scanning examples...done
-Reading examples into memory...100..OK. (150 examples read)
-Setting default regularization parameter C=0.0162
-Optimizing..............................................done. (47 iterations)
-Optimization finished (9 misclassified, maxdiff=0.00047).
-Runtime in cpu-seconds: 0.00
-Number of SV: 83 (including 80 at upper bound)
-L1 loss: loss=45.24874
-Norm of weight vector: |w|=0.76906
-Norm of longest example vector: |x|=11.11126
-Estimated VCdim of classifier: VCdim<=62.16794
-Computing XiAlpha-estimates...done
-Runtime for XiAlpha-estimates in cpu-seconds: 0.00
-XiAlpha-estimate of the error: error<=54.67% (rho=1.00,depth=0)
-XiAlpha-estimate of the recall: recall=>18.00% (rho=1.00,depth=0)
-XiAlpha-estimate of the precision: precision=>18.00% (rho=1.00,depth=0)
-Number of kernel evaluations: 1939
-Writing model file...done
diff --git a/data/iris/svm_light/virginica.model b/data/iris/svm_light/virginica.model
deleted file mode 100644
index ce63e74..0000000
--- a/data/iris/svm_light/virginica.model
+++ /dev/null
@@ -1,94 +0,0 @@
-SVM-light Version V6.02
-0 # kernel type
-3 # kernel parameter -d 
-1 # kernel parameter -g 
-1 # kernel parameter -s 
-1 # kernel parameter -r 
-empty# kernel parameter -u 
-4 # highest feature index 
-150 # number of training documents 
-84 # number of support vectors plus 1 
-5.1687631 # threshold b, each following line is a SV (starting with alpha*y)
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