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: 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

18 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

19 properties

101
Number of instances (rows) of the dataset.
18
Number of attributes (columns) of the dataset.
7
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.
1
Number of numeric attributes.
17
Number of nominal attributes.
83.33
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.35
Average class difference between consecutive instances.
0
Percentage of missing values.
0.18
Number of attributes divided by the number of instances.
5.56
Percentage of numeric attributes.
40.59
Percentage of instances belonging to the most frequent class.
94.44
Percentage of nominal attributes.
41
Number of instances belonging to the most frequent class.
3.96
Percentage of instances belonging to the least frequent class.
4
Number of instances belonging to the least frequent class.
15
Number of binary attributes.

11 tasks

96 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: type
41 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: type
1 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: type
1 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: type
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: type
24 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: type
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: type
24 runs - estimation_procedure: Interleaved Test then Train - target_feature: type
0 runs - target_feature: Foo
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