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

19 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.
14.29
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Average class difference between consecutive instances.
0
Percentage of missing values.
0.01
Number of attributes divided by the number of instances.
71.43
Percentage of numeric attributes.
9.09
Percentage of instances belonging to the most frequent class.
28.57
Percentage of nominal attributes.
90
Number of instances belonging to the most frequent class.
9.09
Percentage of instances belonging to the least frequent class.
90
Number of instances belonging to the least frequent class.
2
Number of binary attributes.

7 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
286 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Class
144 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
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