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colleges_aaup

colleges_aaup

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a lower target value as positive ('P') and all others as negative ('N').

17 features

binaryClass (target)nominal2 unique values
0 missing
FICEnumeric1160 unique values
0 missing
College_name (ignore)nominal1140 unique values
0 missing
Statenominal52 unique values
0 missing
Typenominal4 unique values
0 missing
Average_salary-full_professorsnumeric427 unique values
68 missing
Average_salary-associate_professorsnumeric303 unique values
36 missing
Average_salary-assistant_professorsnumeric235 unique values
24 missing
Average_salary-all_ranksnumeric345 unique values
0 missing
Average_compensation-full_professorsnumeric485 unique values
68 missing
Average_compensation-associate_professorsnumeric373 unique values
36 missing
Average_compensation-assistant_professorsnumeric307 unique values
24 missing
Average_compensation-all_ranksnumeric431 unique values
0 missing
Number_of_full_professorsnumeric298 unique values
0 missing
Number_of_associate_professorsnumeric255 unique values
0 missing
Number_of_assistant_professorsnumeric241 unique values
0 missing
Number_of_instructorsnumeric83 unique values
0 missing

107 properties

1161
Number of instances (rows) of the dataset.
17
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
256
Number of missing values in the dataset.
87
Number of instances with at least one value missing.
13
Number of numeric attributes.
4
Number of nominal attributes.
550.76
Mean of means among attributes of the numeric type.
0.08
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.21
First quartile of kurtosis among attributes of the numeric type.
131.64
Third quartile of standard deviation of attributes of the numeric type.
0.97
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
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.04
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.26
Average mutual information between the nominal attributes and the target attribute.
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
83.74
First quartile of means among attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.03
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
0.05
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
11.71
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.
0.05
First quartile of mutual information between the nominal attributes and the target attribute.
0.06
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
19.33
Average number of distinct values among the attributes of the nominal type.
0.43
First quartile of skewness among attributes of the numeric type.
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.97
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
28.31
Standard deviation of the number of distinct values among attributes of the nominal type.
0.04
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.64
Mean skewness among attributes of the numeric type.
72.17
First quartile of standard deviation of attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
270.61
Mean standard deviation of attributes of the numeric type.
3.34
Second quartile (Median) of entropy among attributes.
0.06
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.92
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
0.11
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
70.03
Percentage of instances belonging to the most frequent class.
1.43
Minimal entropy among attributes.
0.54
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.88
Entropy of the target attribute values.
0.73
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
813
Number of instances belonging to the most frequent class.
5.25
Maximum entropy among attributes.
-0.03
Minimum kurtosis among attributes of the numeric type.
420.37
Second quartile (Median) of means among attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
50.91
Maximum kurtosis among attributes of the numeric type.
12.74
Minimum of means among attributes of the numeric type.
0.26
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.06
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.06
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
3052.05
Maximum of means among attributes of the numeric type.
0.05
Minimal mutual information between the nominal attributes and the target attribute.
0.68
Second quartile (Median) of skewness among attributes of the numeric type.
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.87
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.48
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
5.88
Percentage of binary attributes.
92.29
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.01
Number of attributes divided by the number of instances.
52
The maximum number of distinct values among attributes of the nominal type.
0.34
Minimum skewness among attributes of the numeric type.
7.49
Percentage of instances having missing values.
5.25
Third quartile of entropy among attributes.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
3.35
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
5.82
Maximum skewness among attributes of the numeric type.
19.51
Minimum standard deviation of attributes of the numeric type.
1.3
Percentage of missing values.
9.79
Third quartile of kurtosis among attributes of the numeric type.
0.65
Average class difference between consecutive instances.
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2411.62
Maximum standard deviation of attributes of the numeric type.
29.97
Percentage of instances belonging to the least frequent class.
76.47
Percentage of numeric attributes.
525.42
Third quartile of means among attributes of the numeric type.
0.97
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
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.04
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.34
Average entropy of the attributes.
348
Number of instances belonging to the least frequent class.
23.53
Percentage of nominal attributes.
0.48
Third quartile of mutual information between the nominal attributes and the target attribute.
0.03
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
0.05
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
7.3
Mean kurtosis among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.43
First quartile of entropy among attributes.
2.81
Third quartile of skewness among attributes of the numeric type.
0.92
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
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001

7 tasks

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