Data
visualizing_livestock

visualizing_livestock

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The name of each S data set is the name of the data set used in the book. To find the description of the data set in the book look under the entry - data, name - in the index. For example, one data set is barley. To find the description of barley, look in the index under the entry - data, barley. File: ../data/visualizing/livestock.csv Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific

3 features

livestocktype (target)nominal5 unique values
0 missing
countrynominal26 unique values
0 missing
countnumeric129 unique values
0 missing

107 properties

130
Number of instances (rows) of the dataset.
3
Number of attributes (columns) of the dataset.
5
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.
2
Number of nominal attributes.
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4.7
First quartile of entropy among attributes.
5.5
Third quartile of skewness among attributes of the numeric type.
0.31
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
-0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
37.69
Mean kurtosis among attributes of the numeric type.
0.67
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
37.69
First quartile of kurtosis among attributes of the numeric type.
45105899.03
Third quartile of standard deviation of attributes of the numeric type.
0.69
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
0.38
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.55
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
18212792.31
Mean of means among attributes of the numeric type.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
18212792.31
First quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.55
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
0.99
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0
Average mutual information between the nominal attributes and the target attribute.
0
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.8
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.31
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
-0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
5.5
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.69
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
14.85
Standard deviation of the number of distinct values among attributes of the nominal type.
0.55
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
15.5
Average number of distinct values among the attributes of the nominal type.
45105899.03
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.55
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
0.39
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
5.5
Mean skewness among attributes of the numeric type.
4.7
Second quartile (Median) of entropy among attributes.
0.8
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.31
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
0.98
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
20
Percentage of instances belonging to the most frequent class.
45105899.03
Mean standard deviation of attributes of the numeric type.
37.69
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.32
Entropy of the target attribute values.
-0.22
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
26
Number of instances belonging to the most frequent class.
4.7
Minimal entropy among attributes.
18212792.31
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
4.7
Maximum entropy among attributes.
37.69
Minimum kurtosis among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.8
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.67
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
37.69
Maximum kurtosis among attributes of the numeric type.
18212792.31
Minimum of means among attributes of the numeric type.
5.5
Second quartile (Median) of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
18212792.31
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
45105899.03
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.38
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.02
Number of attributes divided by the number of instances.
0
Maximum mutual information between the nominal attributes and the target attribute.
5
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
4.7
Third quartile of entropy among attributes.
0.99
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.
26
The maximum number of distinct values among attributes of the nominal type.
5.5
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
37.69
Third quartile of kurtosis among attributes of the numeric type.
0.97
Average class difference between consecutive instances.
-0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
5.5
Maximum skewness among attributes of the numeric type.
45105899.03
Minimum standard deviation of attributes of the numeric type.
33.33
Percentage of numeric attributes.
18212792.31
Third quartile of means among attributes of the numeric type.
0.69
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
0.38
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.55
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
45105899.03
Maximum standard deviation of attributes of the numeric type.
20
Percentage of instances belonging to the least frequent class.
66.67
Percentage of nominal attributes.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
0.55
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
0.99
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
4.7
Average entropy of the attributes.
26
Number of instances belonging to the least frequent class.

6 tasks

723 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: livestocktype
176 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: livestocktype
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: livestocktype
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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