From 26c490f404731d053a6205719b6246502c07b449 Mon Sep 17 00:00:00 2001 From: Patrick Simianer
Date: Sat, 14 Jun 2014 16:46:27 +0200 Subject: init --- data/iris/2svmlight.rb | 18 +++ data/iris/Index | 5 + data/iris/bezdekIris.data | 150 ++++++++++++++++++++ data/iris/bezdekIris.setosa-v-rest.data | 150 ++++++++++++++++++++ data/iris/bezdekIris.setosa-v-rest.shuf.data | 150 ++++++++++++++++++++ data/iris/bezdekIris.versicolor-v-rest.data | 150 ++++++++++++++++++++ data/iris/bezdekIris.versicolor-v-rest.shuf.data | 150 ++++++++++++++++++++ data/iris/bezdekIris.virginica-v-rest.data | 150 ++++++++++++++++++++ data/iris/bezdekIris.virginica-v-rest.shuf.data | 150 ++++++++++++++++++++ data/iris/iris.data | 151 +++++++++++++++++++++ data/iris/iris.names | 69 ++++++++++ data/iris/iris.setosa-v-rest.cfg | 2 + data/iris/iris.setosa-v-rest.shuf.model.gz | Bin 0 -> 51 bytes data/iris/iris.versicolor-v-rest.cfg | 2 + data/iris/iris.versicolor-v-rest.shuf.model.gz | Bin 0 -> 67 bytes data/iris/iris.virginica-v-rest.cfg | 2 + data/iris/iris.virginica-v-rest.shuf.model.gz | Bin 0 -> 70 bytes data/iris/svm_light/run.sh | 7 + data/iris/svm_light/setosa.learnout | 18 +++ data/iris/svm_light/setosa.model | 47 +++++++ data/iris/svm_light/svm_predictions | 150 ++++++++++++++++++++ data/iris/svm_light/versicolor-v-rest.model | 112 +++++++++++++++ data/iris/svm_light/versicolor.learnout | 18 +++ data/iris/svm_light/versicolor.model | 112 +++++++++++++++ .../svm_light/virginica-v-rest.shuf.data.model | 94 +++++++++++++ data/iris/svm_light/virginica.learnout | 18 +++ data/iris/svm_light/virginica.model | 94 +++++++++++++ 27 files changed, 1969 insertions(+) create mode 100755 data/iris/2svmlight.rb create mode 100644 data/iris/Index create mode 100644 data/iris/bezdekIris.data create mode 100644 data/iris/bezdekIris.setosa-v-rest.data create mode 100644 data/iris/bezdekIris.setosa-v-rest.shuf.data create mode 100644 data/iris/bezdekIris.versicolor-v-rest.data create mode 100644 data/iris/bezdekIris.versicolor-v-rest.shuf.data create mode 100644 data/iris/bezdekIris.virginica-v-rest.data create mode 100644 data/iris/bezdekIris.virginica-v-rest.shuf.data create mode 100644 data/iris/iris.data create mode 100644 data/iris/iris.names create mode 100644 data/iris/iris.setosa-v-rest.cfg create mode 100644 data/iris/iris.setosa-v-rest.shuf.model.gz create mode 100644 data/iris/iris.versicolor-v-rest.cfg create mode 100644 data/iris/iris.versicolor-v-rest.shuf.model.gz create mode 100644 data/iris/iris.virginica-v-rest.cfg create mode 100644 data/iris/iris.virginica-v-rest.shuf.model.gz create mode 100755 data/iris/svm_light/run.sh create mode 100644 data/iris/svm_light/setosa.learnout create mode 100644 data/iris/svm_light/setosa.model create mode 100644 data/iris/svm_light/svm_predictions create mode 100644 data/iris/svm_light/versicolor-v-rest.model create mode 100644 data/iris/svm_light/versicolor.learnout create mode 100644 data/iris/svm_light/versicolor.model create mode 100644 data/iris/svm_light/virginica-v-rest.shuf.data.model create mode 100644 data/iris/svm_light/virginica.learnout create mode 100644 data/iris/svm_light/virginica.model (limited to 'data/iris') diff --git a/data/iris/2svmlight.rb b/data/iris/2svmlight.rb new file mode 100755 index 0000000..7307262 --- /dev/null +++ b/data/iris/2svmlight.rb @@ -0,0 +1,18 @@ +#!/usr/bin/env ruby + + +label1 = "Iris-"+ARGV[0] + +while line = STDIN.gets + line.strip! + a = line.split ',' + label = -1 + label = 1 if a[-1]==label1 + a = a[0..a.size-2] + f = [] + a.each_with_index { |i,idx| + f<<"#{idx+1}:#{i.to_f}" + } + puts "#{label} #{f.join(' ')}" +end + diff --git a/data/iris/Index b/data/iris/Index new file mode 100644 index 0000000..8c246ed --- /dev/null +++ b/data/iris/Index @@ -0,0 +1,5 @@ +Index of iris + +02 Dec 1996 105 Index +08 Mar 1993 4551 iris.data +30 May 1989 2604 iris.names diff --git a/data/iris/bezdekIris.data b/data/iris/bezdekIris.data new file mode 100644 index 0000000..2bf7d09 --- /dev/null +++ b/data/iris/bezdekIris.data @@ -0,0 +1,150 @@ +5.1,3.5,1.4,0.2,Iris-setosa +4.9,3.0,1.4,0.2,Iris-setosa +4.7,3.2,1.3,0.2,Iris-setosa +4.6,3.1,1.5,0.2,Iris-setosa +5.0,3.6,1.4,0.2,Iris-setosa +5.4,3.9,1.7,0.4,Iris-setosa +4.6,3.4,1.4,0.3,Iris-setosa +5.0,3.4,1.5,0.2,Iris-setosa +4.4,2.9,1.4,0.2,Iris-setosa +4.9,3.1,1.5,0.1,Iris-setosa +5.4,3.7,1.5,0.2,Iris-setosa +4.8,3.4,1.6,0.2,Iris-setosa +4.8,3.0,1.4,0.1,Iris-setosa +4.3,3.0,1.1,0.1,Iris-setosa +5.8,4.0,1.2,0.2,Iris-setosa +5.7,4.4,1.5,0.4,Iris-setosa +5.4,3.9,1.3,0.4,Iris-setosa +5.1,3.5,1.4,0.3,Iris-setosa +5.7,3.8,1.7,0.3,Iris-setosa +5.1,3.8,1.5,0.3,Iris-setosa +5.4,3.4,1.7,0.2,Iris-setosa +5.1,3.7,1.5,0.4,Iris-setosa +4.6,3.6,1.0,0.2,Iris-setosa +5.1,3.3,1.7,0.5,Iris-setosa +4.8,3.4,1.9,0.2,Iris-setosa +5.0,3.0,1.6,0.2,Iris-setosa +5.0,3.4,1.6,0.4,Iris-setosa +5.2,3.5,1.5,0.2,Iris-setosa +5.2,3.4,1.4,0.2,Iris-setosa +4.7,3.2,1.6,0.2,Iris-setosa +4.8,3.1,1.6,0.2,Iris-setosa +5.4,3.4,1.5,0.4,Iris-setosa 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+6.7,3.0,5.2,2.3,Iris-virginica +6.3,2.5,5.0,1.9,Iris-virginica +6.5,3.0,5.2,2.0,Iris-virginica +6.2,3.4,5.4,2.3,Iris-virginica +5.9,3.0,5.1,1.8,Iris-virginica + diff --git a/data/iris/iris.names b/data/iris/iris.names new file mode 100644 index 0000000..062b486 --- /dev/null +++ b/data/iris/iris.names @@ -0,0 +1,69 @@ +1. Title: Iris Plants Database + Updated Sept 21 by C.Blake - Added discrepency information + +2. Sources: + (a) Creator: R.A. Fisher + (b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov) + (c) Date: July, 1988 + +3. Past Usage: + - Publications: too many to mention!!! Here are a few. + 1. Fisher,R.A. "The use of multiple measurements in taxonomic problems" + Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions + to Mathematical Statistics" (John Wiley, NY, 1950). + 2. Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis. + (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218. + 3. Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System + Structure and Classification Rule for Recognition in Partially Exposed + Environments". IEEE Transactions on Pattern Analysis and Machine + Intelligence, Vol. PAMI-2, No. 1, 67-71. + -- Results: + -- very low misclassification rates (0% for the setosa class) + 4. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE + Transactions on Information Theory, May 1972, 431-433. + -- Results: + -- very low misclassification rates again + 5. See also: 1988 MLC Proceedings, 54-64. Cheeseman et al's AUTOCLASS II + conceptual clustering system finds 3 classes in the data. + +4. Relevant Information: + --- This is perhaps the best known database to be found in the pattern + recognition literature. Fisher's paper is a classic in the field + and is referenced frequently to this day. (See Duda & Hart, for + example.) The data set contains 3 classes of 50 instances each, + where each class refers to a type of iris plant. One class is + linearly separable from the other 2; the latter are NOT linearly + separable from each other. + --- Predicted attribute: class of iris plant. + --- This is an exceedingly simple domain. + --- This data differs from the data presented in Fishers article + (identified by Steve Chadwick, spchadwick@espeedaz.net ) + The 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa" + where the error is in the fourth feature. + The 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa" + where the errors are in the second and third features. + +5. Number of Instances: 150 (50 in each of three classes) + +6. Number of Attributes: 4 numeric, predictive attributes and the class + +7. Attribute Information: + 1. sepal length in cm + 2. sepal width in cm + 3. petal length in cm + 4. petal width in cm + 5. class: + -- Iris Setosa + -- Iris Versicolour + -- Iris Virginica + +8. Missing Attribute Values: None + +Summary Statistics: + Min Max Mean SD Class Correlation + sepal length: 4.3 7.9 5.84 0.83 0.7826 + sepal width: 2.0 4.4 3.05 0.43 -0.4194 + petal length: 1.0 6.9 3.76 1.76 0.9490 (high!) + petal width: 0.1 2.5 1.20 0.76 0.9565 (high!) + +9. Class Distribution: 33.3% for each of 3 classes. diff --git a/data/iris/iris.setosa-v-rest.cfg b/data/iris/iris.setosa-v-rest.cfg new file mode 100644 index 0000000..d3c63b8 --- /dev/null +++ b/data/iris/iris.setosa-v-rest.cfg @@ -0,0 +1,2 @@ +train = iris/bezdekIris.setosa-v-rest.shuf.data +model_file=iris/iris.setosa-v-rest.shuf.model.gz diff --git a/data/iris/iris.setosa-v-rest.shuf.model.gz b/data/iris/iris.setosa-v-rest.shuf.model.gz new file mode 100644 index 0000000..07dae81 Binary files /dev/null and b/data/iris/iris.setosa-v-rest.shuf.model.gz differ diff --git a/data/iris/iris.versicolor-v-rest.cfg b/data/iris/iris.versicolor-v-rest.cfg new file mode 100644 index 0000000..a241b28 --- /dev/null +++ b/data/iris/iris.versicolor-v-rest.cfg @@ -0,0 +1,2 @@ +train = iris/bezdekIris.versicolor-v-rest.shuf.data +model_file=iris/iris.versicolor-v-rest.shuf.model.gz diff --git a/data/iris/iris.versicolor-v-rest.shuf.model.gz b/data/iris/iris.versicolor-v-rest.shuf.model.gz new file mode 100644 index 0000000..44a1cab Binary files /dev/null and b/data/iris/iris.versicolor-v-rest.shuf.model.gz differ diff --git a/data/iris/iris.virginica-v-rest.cfg b/data/iris/iris.virginica-v-rest.cfg new file mode 100644 index 0000000..a3f68a0 --- /dev/null +++ b/data/iris/iris.virginica-v-rest.cfg @@ -0,0 +1,2 @@ +train = iris/bezdekIris.virginica-v-rest.shuf.data +model_file=iris/iris.virginica-v-rest.shuf.model.gz diff --git a/data/iris/iris.virginica-v-rest.shuf.model.gz b/data/iris/iris.virginica-v-rest.shuf.model.gz new file mode 100644 index 0000000..3d8b466 Binary files /dev/null and b/data/iris/iris.virginica-v-rest.shuf.model.gz differ diff --git a/data/iris/svm_light/run.sh b/data/iris/svm_light/run.sh new file mode 100755 index 0000000..9040912 --- /dev/null +++ b/data/iris/svm_light/run.sh @@ -0,0 +1,7 @@ +#!/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 new file mode 100644 index 0000000..b5ff56e --- /dev/null +++ b/data/iris/svm_light/setosa.learnout @@ -0,0 +1,18 @@ +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 new file mode 100644 index 0000000..139fa72 --- /dev/null +++ b/data/iris/svm_light/setosa.model @@ -0,0 +1,47 @@ +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 # 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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 # 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+-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 new file mode 100644 index 0000000..f2130b5 --- /dev/null +++ b/data/iris/svm_light/versicolor.learnout @@ -0,0 +1,18 @@ +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 new file mode 100644 index 0000000..e2f8f03 --- /dev/null +++ b/data/iris/svm_light/versicolor.model @@ -0,0 +1,112 @@ +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 # 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(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 new file mode 100644 index 0000000..ce63e74 --- /dev/null +++ b/data/iris/svm_light/virginica.model @@ -0,0 +1,94 @@ +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 # 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