Data
MagicTelescope

MagicTelescope

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/

11 features

class: (target)nominal2 unique values
0 missing
ID (row identifier)numeric19020 unique values
0 missing
fLength:numeric18643 unique values
0 missing
fWidth:numeric18200 unique values
0 missing
fSize:numeric7228 unique values
0 missing
fConc:numeric6410 unique values
0 missing
fConc1:numeric4421 unique values
0 missing
fAsym:numeric18704 unique values
0 missing
fM3Long:numeric18693 unique values
0 missing
fM3Trans:numeric18390 unique values
0 missing
fAlpha:numeric17981 unique values
0 missing
fDist:numeric18437 unique values
0 missing

107 properties

19020
Number of instances (rows) of the dataset.
11
Number of attributes (columns) of the dataset.
2
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.
10
Number of numeric attributes.
1
Number of nominal attributes.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.86
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.16
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
-0.17
First quartile of skewness among attributes of the numeric type.
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.18
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
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.65
Mean skewness among attributes of the numeric type.
0.4
First quartile of standard deviation of attributes of the numeric type.
0.15
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.59
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
0.2
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
64.84
Percentage of instances belonging to the most frequent class.
29.33
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.94
Entropy of the target attribute values.
0.56
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
12332
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
2.7
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.53
Minimum kurtosis among attributes of the numeric type.
6.69
Second quartile (Median) of means among attributes of the numeric type.
0.15
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.28
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
16.77
Maximum kurtosis among attributes of the numeric type.
-4.33
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
193.82
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.59
Second quartile (Median) of skewness among attributes of the numeric type.
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
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.
23.47
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.19
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.
2
The maximum number of distinct values among attributes of the nominal type.
-1.12
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.37
Maximum skewness among attributes of the numeric type.
0.11
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
8.26
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.16
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
74.73
Maximum standard deviation of attributes of the numeric type.
35.16
Percentage of instances belonging to the least frequent class.
90.91
Percentage of numeric attributes.
34.05
Third quartile of means among attributes of the numeric type.
0.86
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
6688
Number of instances belonging to the least frequent class.
9.09
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.18
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
0.59
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
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
4.27
Mean kurtosis among attributes of the numeric type.
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
1.16
Third quartile of skewness among attributes of the numeric type.
0.86
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
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.16
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
30.68
Mean of means among attributes of the numeric type.
0.27
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.21
First quartile of kurtosis among attributes of the numeric type.
53.05
Third quartile of standard deviation of attributes of the numeric type.
0.18
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.24
First quartile of means among attributes of the numeric type.
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.15
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.59
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
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.85
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.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.

11 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class:
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: class:
0 runs - estimation_procedure: 10% Holdout set - target_feature: class:
0 runs - estimation_procedure: 33% Holdout set - target_feature: class:
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: class:
0 runs - estimation_procedure: Test on Training Data - target_feature: class:
0 runs - estimation_procedure: Leave one out - target_feature: class:
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: class:
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class:
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: class:
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class:
Define a new task