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flags

flags

active ARFF Publicly available Visibility: public Uploaded 14-08-2014 by Joaquin Vanschoren
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Author: Richard S. Forsyth Source: Unknown - 5/15/1990 Please cite: ARFF version of UCI dataset 'flags'. Creators: Collected primarily from the "Collins Gem Guide to Flags": Collins Publishers (1986). Donor: Richard S. Forsyth. Date 5/15/1990 This data file contains details of various nations and their flags. With this data you can try things like predicting the religion of a country from its size and the colours in its flag. 10 attributes are numeric-valued. The remainder are either Boolean- or nominal-valued. Number of Instances: 194. Number of attributes: 30 (overall). Missing values: none Attribute Information: 1. name Name of the country concerned 2. landmass 1=N.America, 2=S.America, 3=Europe, 4=Africa, 4=Asia, 6=Oceania 3. zone Geographic quadrant, based on Greenwich and the Equator 1=NE, 2=SE, 3=SW, 4=NW 4. area in thousands of square km 5. population in round millions 6. language 1=English, 2=Spanish, 3=French, 4=German, 5=Slavic, 6=Other Indo-European, 7=Chinese, 8=Arabic, 9=Japanese/Turkish/Finnish/Magyar, 10=Others 7. religion 0=Catholic, 1=Other Christian, 2=Muslim, 3=Buddhist, 4=Hindu, 5=Ethnic, 6=Marxist, 7=Others 8. bars Number of vertical bars in the flag 9. stripes Number of horizontal stripes in the flag 10. colours Number of different colours in the flag 11. red 0 if red absent, 1 if red present in the flag 12. green same for green 13. blue same for blue 14. gold same for gold (also yellow) 15. white same for white 16. black same for black 17. orange same for orange (also brown) 18. mainhue predominant colour in the flag (tie-breaks decided by taking the topmost hue, if that fails then the most central hue, and if that fails the leftmost hue) 19. circles Number of circles in the flag 20. crosses Number of (upright) crosses 21. saltires Number of diagonal crosses 22. quarters Number of quartered sections 23. sunstars Number of sun or star symbols 24. crescent 1 if a crescent moon symbol present, else 0 25. triangle 1 if any triangles present, 0 otherwise 26. icon 1 if an inanimate image present (e.g., a boat), otherwise 0 27. animate 1 if an animate image (e.g., an eagle, a tree, a human hand) present, 0 otherwise 28. text 1 if any letters or writing on the flag (e.g., a motto or slogan), 0 otherwise 29. topleft colour in the top-left corner (moving right to decide tie-breaks) 30. botright Colour in the bottom-left corner (moving left to decide tie-breaks)

30 features

religion (target)nominal8 unique values
0 missing
name (row identifier)nominal194 unique values
0 missing
1landmassnominal6 unique values
0 missing
2zonenominal4 unique values
0 missing
3areanumeric136 unique values
0 missing
populationnumeric48 unique values
0 missing
languagenominal10 unique values
0 missing
barsnominal5 unique values
0 missing
stripesnominal12 unique values
0 missing
coloursnominal8 unique values
0 missing
rednominal2 unique values
0 missing
greennominal2 unique values
0 missing
bluenominal2 unique values
0 missing
goldnominal2 unique values
0 missing
whitenominal2 unique values
0 missing
blacknominal2 unique values
0 missing
orangenominal2 unique values
0 missing
mainhuenominal8 unique values
0 missing
circlesnominal4 unique values
0 missing
crossesnominal3 unique values
0 missing
saltiresnominal2 unique values
0 missing
quartersnominal3 unique values
0 missing
sunstarsnominal14 unique values
0 missing
crescentnominal2 unique values
0 missing
trianglenominal2 unique values
0 missing
iconnominal2 unique values
0 missing
animatenominal2 unique values
0 missing
textnominal2 unique values
0 missing
topleftnominal7 unique values
0 missing
botrightnominal8 unique values
0 missing

107 properties

194
Number of instances (rows) of the dataset.
30
Number of attributes (columns) of the dataset.
8
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.
2
Number of numeric attributes.
28
Number of nominal attributes.
56.45
First quartile of kurtosis among attributes of the numeric type.
2170.93
Third quartile of standard deviation of attributes of the numeric type.
0.83
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
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.41
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
361.66
Mean of means among attributes of the numeric type.
0.4
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
23.27
First quartile of means among attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.4
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
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.23
Average mutual information between the nominal attributes and the target attribute.
0.5
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.05
First quartile of mutual information between the nominal attributes and the target attribute.
0.41
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.51
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
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
4.54
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
13
Number of binary attributes.
6.76
First quartile of skewness among attributes of the numeric type.
0.48
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.83
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
3.51
Standard deviation of the number of distinct values among attributes of the nominal type.
0.41
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
4.67
Average number of distinct values among the attributes of the nominal type.
91.93
First quartile of standard deviation of attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.4
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
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
7.66
Mean skewness among attributes of the numeric type.
0.89
Second quartile (Median) of entropy among attributes.
0.41
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.51
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
0.45
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
30.93
Percentage of instances belonging to the most frequent class.
1131.43
Mean standard deviation of attributes of the numeric type.
69.25
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.48
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.55
Entropy of the target attribute values.
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
60
Number of instances belonging to the most frequent class.
0.31
Minimal entropy among attributes.
361.66
Second quartile (Median) of means among attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
2.88
Maximum entropy among attributes.
56.45
Minimum kurtosis among attributes of the numeric type.
0.13
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.41
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.59
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
82.05
Maximum kurtosis among attributes of the numeric type.
23.27
Minimum of means among attributes of the numeric type.
7.66
Second quartile (Median) of skewness among attributes of the numeric type.
0.48
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
700.05
Maximum of means among attributes of the numeric type.
0.02
Minimal mutual information between the nominal attributes and the target attribute.
1131.43
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.15
Number of attributes divided by the number of instances.
1.13
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
43.33
Percentage of binary attributes.
1.99
Third quartile of entropy among attributes.
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
11.32
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
14
The maximum number of distinct values among attributes of the nominal type.
6.76
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
82.05
Third quartile of kurtosis among attributes of the numeric type.
0.24
Average class difference between consecutive instances.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
8.57
Maximum skewness among attributes of the numeric type.
91.93
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
700.05
Third quartile of means among attributes of the numeric type.
0.83
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
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.41
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2170.93
Maximum standard deviation of attributes of the numeric type.
2.06
Percentage of instances belonging to the least frequent class.
6.67
Percentage of numeric attributes.
0.29
Third quartile of mutual information between the nominal attributes and the target attribute.
0.4
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
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.25
Average entropy of the attributes.
4
Number of instances belonging to the least frequent class.
93.33
Percentage of nominal attributes.
0.63
First quartile of entropy among attributes.
8.57
Third quartile of skewness among attributes of the numeric type.
0.51
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
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
69.25
Mean kurtosis among attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

9 tasks

103 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: religion
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: religion
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: religion
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: religion
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - target_feature: a
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