Data
zoo

zoo

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Author: Richard S. Forsyth Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Zoo) - 5/15/1990 Please cite: [UCI Citation Policy](https://archive.ics.uci.edu/ml/citation_policy.html) Zoo database A simple database containing 17 Boolean-valued attributes describing animals. The "type" attribute appears to be the class attribute. Notes: * I find it unusual that there are 2 instances of "frog" and one of "girl"! * feature 'animal' is an identifier (though not unique) and should be ignored when modeling ### Data Set Information: A simple database containing 17 Boolean-valued attributes. The "type" attribute appears to be the class attribute. Here is a breakdown of which animals are in which type: (I find it unusual that there are 2 instances of "frog" and one of "girl"!) Class# -- Set of animals: ====== ==================================================== 1 -- (41) aardvark, antelope, bear, boar, buffalo, calf, cavy, cheetah, deer, dolphin, elephant, fruitbat, giraffe, girl, goat, gorilla, hamster, hare, leopard, lion, lynx, mink, mole, mongoose, opossum, oryx, platypus, polecat, pony, porpoise, puma, pussycat, raccoon, reindeer, seal, sealion, squirrel, vampire, vole, wallaby,wolf 2 -- (20) chicken, crow, dove, duck, flamingo, gull, hawk, kiwi, lark, ostrich, parakeet, penguin, pheasant, rhea, skimmer, skua, sparrow, swan, vulture, wren 3 -- (5) pitviper, seasnake, slowworm, tortoise, tuatara 4 -- (13) bass, carp, catfish, chub, dogfish, haddock, herring, pike, piranha, seahorse, sole, stingray, tuna 5 -- (4) frog, frog, newt, toad 6 -- (8) flea, gnat, honeybee, housefly, ladybird, moth, termite, wasp 7 -- (10) clam, crab, crayfish, lobster, octopus, scorpion, seawasp, slug, starfish, worm ### Attribute Information: 1. animal name: Unique for each instance 2. hair: Boolean 3. feathers: Boolean 4. eggs: Boolean 5. milk: Boolean 6. airborne: Boolean 7. aquatic: Boolean 8. predator: Boolean 9. toothed: Boolean 10. backbone: Boolean 11. breathes: Boolean 12. venomous: Boolean 13. fins: Boolean 14. legs: Numeric (set of values: {0,2,4,5,6,8}) 15. tail: Boolean 16. domestic: Boolean 17. catsize: Boolean 18. type: Numeric (integer values in range [1,7])

17 features

type (target)nominal7 unique values
0 missing
animal (ignore)nominal100 unique values
0 missing
hairnominal2 unique values
0 missing
feathersnominal2 unique values
0 missing
eggsnominal2 unique values
0 missing
milknominal2 unique values
0 missing
airbornenominal2 unique values
0 missing
aquaticnominal2 unique values
0 missing
predatornominal2 unique values
0 missing
toothednominal2 unique values
0 missing
backbonenominal2 unique values
0 missing
breathesnominal2 unique values
0 missing
venomousnominal2 unique values
0 missing
finsnominal2 unique values
0 missing
legsnumeric6 unique values
0 missing
tailnominal2 unique values
0 missing
domesticnominal2 unique values
0 missing
catsizenominal2 unique values
0 missing
Show all 17 features

107 properties

NumberOfInstances
101
Number of instances (rows) of the dataset.
NumberOfFeatures
17
Number of attributes (columns) of the dataset.
NumberOfClasses
7
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
1
Number of numeric attributes.
NumberOfSymbolicFeatures
16
Number of nominal attributes.
Quartile1StdDevOfNumericAtts
2.03
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2AUC
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NErrRate
0.03
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
kNN1NAUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.84
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanSkewnessOfNumericAtts
0.14
Mean skewness among attributes of the numeric type.
Quartile2AttributeEntropy
0.82
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.96
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
kNN1NErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
40.59
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
2.03
Mean standard deviation of attributes of the numeric type.
Quartile2KurtosisOfNumericAtts
-0.6
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth2Kappa
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
2.39
Entropy of the target attribute values.
kNN1NKappa
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
41
Number of instances belonging to the most frequent class.
MinAttributeEntropy
0.4
Minimal entropy among attributes.
Quartile2MeansOfNumericAtts
2.84
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
0.99
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-0.6
Minimum kurtosis among attributes of the numeric type.
Quartile2MutualInformation
0.5
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
REPTreeDepth3ErrRate
0.2
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.41
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
-0.6
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
2.84
Minimum of means among attributes of the numeric type.
Quartile2SkewnessOfNumericAtts
0.14
Second quartile (Median) of skewness among attributes of the numeric type.
REPTreeDepth3Kappa
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
2.84
Maximum of means among attributes of the numeric type.
MinMutualInformation
0.05
Minimal mutual information between the nominal attributes and the target attribute.
Quartile2StdDevOfNumericAtts
2.03
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
0.17
Number of attributes divided by the number of instances.
MaxMutualInformation
0.97
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfBinaryFeatures
88.24
Percentage of binary attributes.
Quartile3AttributeEntropy
0.98
Third quartile of entropy among attributes.
RandomTreeDepth1ErrRate
0.41
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
4.55
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
7
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
0.14
Minimum skewness among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3KurtosisOfNumericAtts
-0.6
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
0.35
Average class difference between consecutive instances.
RandomTreeDepth1Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
0.14
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
2.03
Minimum standard deviation of attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
5.88
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
2.84
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
0.82
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
RandomTreeDepth2AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
2.03
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
3.96
Percentage of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
94.12
Percentage of nominal attributes.
Quartile3MutualInformation
0.79
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
0.41
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
RandomTreeDepth2ErrRate
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
0.81
Average entropy of the attributes.
MinorityClassSize
4
Number of instances belonging to the least frequent class.
Quartile1AttributeEntropy
0.68
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
0.14
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
0.43
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
RandomTreeDepth2Kappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
-0.6
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
-0.6
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
2.03
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
1
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
RandomTreeDepth3AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.15
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
2.84
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
2.84
First quartile of means among attributes of the numeric type.
REPTreeDepth1AUC
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
0.06
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
RandomTreeDepth3ErrRate
0.18
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
0.53
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MutualInformation
0.31
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
0.41
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.92
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
RandomTreeDepth3Kappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNoiseToSignalRatio
0.55
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
15
Number of binary attributes.
Quartile1SkewnessOfNumericAtts
0.14
First quartile of skewness among attributes of the numeric type.
REPTreeDepth1Kappa
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NAUC
0.99
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
StdvNominalAttDistinctValues
1.25
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
2.31
Average number of distinct values among the attributes of the nominal type.
Show all 107 properties

20 tasks

Supervised Classification on zoo
80 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: type
Supervised Classification on zoo
40 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: type
Supervised Classification on zoo
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: type
Supervised Classification on zoo
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: type
Supervised Classification on zoo
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: type
Learning Curve on zoo
29 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: type
Learning Curve on zoo
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: type
Supervised Data Stream Classification on zoo
24 runs - estimation_procedure: Interleaved Test then Train - target_feature: type
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - target_feature: Foo
Clustering on zoo
0 runs
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
Clustering on zoo
0 runs - estimation_procedure: 50 times Clustering
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