Data
analcatdata_bondrate

analcatdata_bondrate

active ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
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A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. Further details concerning the book, including information on statistical software (including sample S-PLUS/R and SAS code), are available [here](http://www.stern.nyu.edu/~jsimonof/AnalCatData) Information about the dataset\ CLASSTYPE: nominal\ CLASSINDEX: last Note: Quotes, Single-Quotes and Backslashes were removed, Blanks replaced with Underscores

11 features

Rating (target)nominal5 unique values
0 missing
City (ignore)nominal57 unique values
0 missing
Populationnumeric56 unique values
1 missing
Per_capita_incomenumeric56 unique values
0 missing
Household_incomenumeric56 unique values
0 missing
Discretionary_incomenumeric55 unique values
0 missing
Publics_in_top_10nominal10 unique values
0 missing
Nonprofits_in_top_10nominal6 unique values
0 missing
For_profits_in_top_10nominal9 unique values
0 missing
Utilities_in_top_10nominal3 unique values
0 missing
Regionnominal4 unique values
0 missing
State_capitalnominal2 unique values
0 missing

107 properties

57
Number of instances (rows) of the dataset.
11
Number of attributes (columns) of the dataset.
5
Number of distinct values of the target attribute (if it is nominal).
1
Number of missing values in the dataset.
1
Number of instances with at least one value missing.
4
Number of numeric attributes.
7
Number of nominal attributes.
2920.39
First quartile of standard deviation of attributes of the numeric type.
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.42
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
0.52
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.28
Mean skewness among attributes of the numeric type.
2.1
Second quartile (Median) of entropy among attributes.
0.51
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0
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
0.54
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
57.89
Percentage of instances belonging to the most frequent class.
788385.22
Mean standard deviation of attributes of the numeric type.
0.71
Second quartile (Median) of kurtosis among attributes of the numeric type.
-0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1.68
Entropy of the target attribute values.
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
33
Number of instances belonging to the most frequent class.
0.83
Minimal entropy among attributes.
49782.25
Second quartile (Median) of means among attributes of the numeric type.
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
2.99
Maximum entropy among attributes.
-0.16
Minimum kurtosis among attributes of the numeric type.
0.33
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.51
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.46
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
14.35
Maximum kurtosis among attributes of the numeric type.
16569.95
Minimum of means among attributes of the numeric type.
0.74
Second quartile (Median) of skewness among attributes of the numeric type.
-0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
-0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
2315386.25
Maximum of means among attributes of the numeric type.
0.06
Minimal mutual information between the nominal attributes and the target attribute.
6730.82
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.19
Number of attributes divided by the number of instances.
0.41
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
9.09
Percentage of binary attributes.
2.77
Third quartile of entropy among attributes.
0.56
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
6.22
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10
The maximum number of distinct values among attributes of the nominal type.
0.08
Minimum skewness among attributes of the numeric type.
1.75
Percentage of instances having missing values.
10.97
Third quartile of kurtosis among attributes of the numeric type.
0.38
Average class difference between consecutive instances.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.48
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.57
Maximum skewness among attributes of the numeric type.
2094.43
Minimum standard deviation of attributes of the numeric type.
0.16
Percentage of missing values.
1750349.91
Third quartile of means among attributes of the numeric type.
0.48
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
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.42
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3137984.79
Maximum standard deviation of attributes of the numeric type.
1.75
Percentage of instances belonging to the least frequent class.
36.36
Percentage of numeric attributes.
0.41
Third quartile of mutual information between the nominal attributes and the target attribute.
0.42
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
0.56
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.95
Average entropy of the attributes.
1
Number of instances belonging to the least frequent class.
63.64
Percentage of nominal attributes.
2.91
Third quartile of skewness among attributes of the numeric type.
0
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.48
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
3.9
Mean kurtosis among attributes of the numeric type.
0.49
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.94
First quartile of entropy among attributes.
2355504.44
Third quartile of standard deviation of attributes of the numeric type.
0.48
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
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.42
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
607880.18
Mean of means among attributes of the numeric type.
0.63
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.03
First quartile of kurtosis among attributes of the numeric type.
23508.36
First quartile of means among attributes of the numeric type.
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.42
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
0.56
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.27
Average mutual information between the nominal attributes and the target attribute.
-0.02
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.08
First quartile of mutual information between the nominal attributes and the target attribute.
0.51
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.48
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
6.21
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
1
Number of binary attributes.
0.2
First quartile of skewness among attributes of the numeric type.
-0.02
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.48
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
2.99
Standard deviation of the number of distinct values among attributes of the nominal type.
0.42
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
5.57
Average number of distinct values among the attributes of the nominal type.

14 tasks

32 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Rating
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Rating
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Rating
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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