Data
vowel

vowel

deactivated ARFF Publicly available Visibility: public Uploaded 06-04-2014 by Jan van Rijn
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Author: Source: Unknown - Please cite: * Please use version 2 of this dataset. This version has a train/test feature that should be ignored in OpenML. Introduction ============ In my work on context-sensitive learning, I used the "Deterding Vowel Recognition Data", but I found it necessary to reformulate the data. Implicit in the original data is contextual information on the speaker's gender and identity. For my work, it was necessary to make this information explicit. The file "vowel-context.data" adds the speaker's sex and identity as new features. The format of the data file is described below. Peter Turney peter@ai.iit.nrc.ca References ========== P. Turney. "Robust Classification With Context-Sensitive Features." Proceedings of the Sixth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-93): 268-276. 1993. URL: ftp://ai.iit.nrc.ca/pub/ksl-papers/NRC-35074.ps.Z P. Turney. "Exploiting Context When Learning to Classify." Proceedings of the European Conference on Machine Learning (ECML-93): 402-407. 1993. URL: ftp://ai.iit.nrc.ca/pub/ksl-papers/NRC-35058.ps.Z File Structure ============== Column Description ------------------------------- 0 Train or Test 1 Speaker Number 2 Sex 3 Feature 0 4 Feature 1 5 Feature 2 6 Feature 3 7 Feature 4 8 Feature 5 9 Feature 6 10 Feature 7 11 Feature 8 12 Feature 9 13 Class Numerical Codes =============== Speaker Code Number --------------------------- Andrew 0 Bill 1 David 2 Mark 3 Jo 4 Kate 5 Penny 6 Rose 7 Mike 8 Nick 9 Rich 10 Tim 11 Sarah 12 Sue 13 Wendy 14 Set Number --------------------------- Train 0 Test 1 Sex Number --------------------------- Male 0 Female 1 Class Number --------------------------- hid 0 hId 1 hEd 2 hAd 3 hYd 4 had 5 hOd 6 hod 7 hUd 8 hud 9 hed 10 Speaker Code Number Sex Train/Test --------------------------------------------------------------- Andrew 0 0 0 Bill 1 0 0 David 2 0 0 Mark 3 0 0 Jo 4 1 0 Kate 5 1 0 Penny 6 1 0 Rose 7 1 0 Mike 8 0 1 Nick 9 0 1 Rich 10 0 1 Tim 11 0 1 Sarah 12 1 1 Sue 13 1 1 Wendy 14 1 1 Num Instances: 990 Num Attributes: 14 Num missing: 0 / 0.0% name type enum ints real missing distinct (1) 1 'Train or Test' Enum 100% 0% 0% 0 / 0% 2 / 0% 0% 2 'Speaker Number' Enum 0% 100% 0% 0 / 0% 15 / 2% 0% 3 'Sex' Enum 0% 100% 0% 0 / 0% 2 / 0% 0% 4 'Feature 0' Real 0% 0% 100% 0 / 0% 853 / 86% 74% 5 'Feature 1' Real 0% 0% 100% 0 / 0% 877 / 89% 78% 6 'Feature 2' Real 0% 0% 100% 0 / 0% 815 / 82% 67% 7 'Feature 3' Real 0% 0% 100% 0 / 0% 836 / 84% 71% 8 'Feature 4' Real 0% 0% 100% 0 / 0% 803 / 81% 66% 9 'Feature 5' Real 0% 0% 100% 0 / 0% 798 / 81% 64% 10 'Feature 6' Real 0% 0% 100% 0 / 0% 748 / 76% 57% 11 'Feature 7' Real 0% 0% 100% 0 / 0% 794 / 80% 64% 12 'Feature 8' Real 0% 0% 100% 0 / 0% 788 / 80% 63% 13 'Feature 9' Real 0% 0% 100% 0 / 0% 775 / 78% 60% 14 'Class' Enum 0% 100% 0% 0 / 0% 11 / 1% 0% Relabeled values in attribute 'Speaker Number' From: 0 To: Andrew From: 1 To: Bill From: 2 To: David From: 3 To: Mark From: 4 To: Jo From: 5 To: Kate From: 6 To: Penny From: 7 To: Rose From: 8 To: Mike From: 9 To: Nick From: 10 To: Rich From: 11 To: Tim From: 12 To: Sarah From: 13 To: Sue From: 14 To: Wendy Relabeled values in attribute 'Sex' From: 0 To: Male From: 1 To: Female Relabeled values in attribute 'Class' From: 0 To: hid From: 1 To: hId From: 2 To: hEd From: 3 To: hAd From: 4 To: hYd From: 5 To: had From: 6 To: hOd From: 7 To: hod From: 8 To: hUd From: 9 To: hud From: 10 To: hed

14 features

Class (target)nominal11 unique values
0 missing
Train_or_Testnominal2 unique values
0 missing
Speaker_Numbernominal15 unique values
0 missing
Sexnominal2 unique values
0 missing
Feature_0numeric853 unique values
0 missing
Feature_1numeric877 unique values
0 missing
Feature_2numeric815 unique values
0 missing
Feature_3numeric836 unique values
0 missing
Feature_4numeric803 unique values
0 missing
Feature_5numeric798 unique values
0 missing
Feature_6numeric748 unique values
0 missing
Feature_7numeric794 unique values
0 missing
Feature_8numeric788 unique values
0 missing
Feature_9numeric775 unique values
0 missing

107 properties

990
Number of instances (rows) of the dataset.
14
Number of attributes (columns) of the dataset.
11
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
10
Number of numeric attributes.
4
Number of nominal attributes.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.64
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
7.5
Average number of distinct values among the attributes of the nominal type.
-0.01
First quartile of skewness among attributes of the numeric type.
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
6.56
Standard deviation of the number of distinct values among attributes of the nominal type.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.09
Mean skewness among attributes of the numeric type.
0.57
First quartile of standard deviation of attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.31
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.7
Mean standard deviation of attributes of the numeric type.
1
Second quartile (Median) of entropy among attributes.
0.64
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.08
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
9.09
Percentage of instances belonging to the most frequent class.
1
Minimal entropy among attributes.
-0.43
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.46
Entropy of the target attribute values.
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
90
Number of instances belonging to the most frequent class.
-0.76
Minimum kurtosis among attributes of the numeric type.
-0.04
Second quartile (Median) of means among attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
3.91
Maximum entropy among attributes.
-3.2
Minimum of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.64
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.82
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.15
Maximum kurtosis among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0.06
Second quartile (Median) of skewness among attributes of the numeric type.
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.09
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
1.88
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
14.29
Percentage of binary attributes.
0.63
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.01
Number of attributes divided by the number of instances.
0
Maximum mutual information between the nominal attributes and the target attribute.
-0.21
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
3.91
Third quartile of entropy among attributes.
0.32
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
15
The maximum number of distinct values among attributes of the nominal type.
0.46
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
-0.24
Third quartile of kurtosis among attributes of the numeric type.
0
Average class difference between consecutive instances.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.36
Maximum skewness among attributes of the numeric type.
9.09
Percentage of instances belonging to the least frequent class.
71.43
Percentage of numeric attributes.
0.54
Third quartile of means among attributes of the numeric type.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.31
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.18
Maximum standard deviation of attributes of the numeric type.
90
Number of instances belonging to the least frequent class.
28.57
Percentage of nominal attributes.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.32
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.97
Average entropy of the attributes.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1
First quartile of entropy among attributes.
0.25
Third quartile of skewness among attributes of the numeric type.
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.39
Mean kurtosis among attributes of the numeric type.
0.42
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.56
First quartile of kurtosis among attributes of the numeric type.
0.79
Third quartile of standard deviation of attributes of the numeric type.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.31
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.1
Mean of means among attributes of the numeric type.
0
Average mutual information between the nominal attributes and the target attribute.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.36
First quartile of means among attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.31
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.32
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

6 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
288 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Class
248 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Class
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
Define a new task