Data
spectrometer

spectrometer

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). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and all others as negative ('N'). Originally converted by Quan Sun.

103 features

binaryClass (target)nominal2 unique values
0 missing
LRS-name (ignore)nominal531 unique values
0 missing
ID-typenominal4 unique values
0 missing
Right-Ascensionnumeric518 unique values
0 missing
Declinationnumeric530 unique values
0 missing
Scale_Factornumeric1 unique values
0 missing
Blue_base_1numeric461 unique values
0 missing
Blue_base_2numeric468 unique values
0 missing
Red_base_1numeric426 unique values
0 missing
Red_base_2numeric417 unique values
0 missing
blue-band-flux_1numeric531 unique values
0 missing
blue-band-flux_2numeric531 unique values
0 missing
blue-band-flux_3numeric531 unique values
0 missing
blue-band-flux_4numeric531 unique values
0 missing
blue-band-flux_5numeric531 unique values
0 missing
blue-band-flux_6numeric531 unique values
0 missing
blue-band-flux_7numeric531 unique values
0 missing
blue-band-flux_8numeric531 unique values
0 missing
blue-band-flux_9numeric531 unique values
0 missing
blue-band-flux_10numeric531 unique values
0 missing
blue-band-flux_11numeric531 unique values
0 missing
blue-band-flux_12numeric531 unique values
0 missing
blue-band-flux_13numeric531 unique values
0 missing
blue-band-flux_14numeric531 unique values
0 missing
blue-band-flux_15numeric531 unique values
0 missing
blue-band-flux_16numeric530 unique values
0 missing
blue-band-flux_17numeric531 unique values
0 missing
blue-band-flux_18numeric531 unique values
0 missing
blue-band-flux_19numeric531 unique values
0 missing
blue-band-flux_20numeric531 unique values
0 missing
blue-band-flux_21numeric531 unique values
0 missing
blue-band-flux_22numeric531 unique values
0 missing
blue-band-flux_23numeric531 unique values
0 missing
blue-band-flux_24numeric531 unique values
0 missing
blue-band-flux_25numeric531 unique values
0 missing
blue-band-flux_26numeric531 unique values
0 missing
blue-band-flux_27numeric531 unique values
0 missing
blue-band-flux_28numeric531 unique values
0 missing
blue-band-flux_29numeric531 unique values
0 missing
blue-band-flux_30numeric531 unique values
0 missing
blue-band-flux_31numeric531 unique values
0 missing
blue-band-flux_32numeric531 unique values
0 missing
blue-band-flux_33numeric531 unique values
0 missing
blue-band-flux_34numeric531 unique values
0 missing
blue-band-flux_35numeric531 unique values
0 missing
blue-band-flux_36numeric531 unique values
0 missing
blue-band-flux_37numeric531 unique values
0 missing
blue-band-flux_38numeric531 unique values
0 missing
blue-band-flux_39numeric531 unique values
0 missing
blue-band-flux_40numeric531 unique values
0 missing
blue-band-flux_41numeric531 unique values
0 missing
blue-band-flux_42numeric531 unique values
0 missing
blue-band-flux_43numeric531 unique values
0 missing
blue-band-flux_44numeric531 unique values
0 missing
red-band-flux_1numeric531 unique values
0 missing
red-band-flux_2numeric531 unique values
0 missing
red-band-flux_3numeric531 unique values
0 missing
red-band-flux_4numeric531 unique values
0 missing
red-band-flux_5numeric531 unique values
0 missing
red-band-flux_6numeric531 unique values
0 missing
red-band-flux_7numeric531 unique values
0 missing
red-band-flux_8numeric531 unique values
0 missing
red-band-flux_9numeric531 unique values
0 missing
red-band-flux_10numeric531 unique values
0 missing
red-band-flux_11numeric531 unique values
0 missing
red-band-flux_12numeric531 unique values
0 missing
red-band-flux_13numeric531 unique values
0 missing
red-band-flux_14numeric531 unique values
0 missing
red-band-flux_15numeric531 unique values
0 missing
red-band-flux_16numeric531 unique values
0 missing
red-band-flux_17numeric531 unique values
0 missing
red-band-flux_18numeric531 unique values
0 missing
red-band-flux_19numeric531 unique values
0 missing
red-band-flux_20numeric531 unique values
0 missing
red-band-flux_21numeric531 unique values
0 missing
red-band-flux_22numeric531 unique values
0 missing
red-band-flux_23numeric531 unique values
0 missing
red-band-flux_24numeric531 unique values
0 missing
red-band-flux_25numeric531 unique values
0 missing
red-band-flux_26numeric531 unique values
0 missing
red-band-flux_27numeric531 unique values
0 missing
red-band-flux_28numeric531 unique values
0 missing
red-band-flux_29numeric531 unique values
0 missing
red-band-flux_30numeric531 unique values
0 missing
red-band-flux_31numeric531 unique values
0 missing
red-band-flux_32numeric531 unique values
0 missing
red-band-flux_33numeric531 unique values
0 missing
red-band-flux_34numeric531 unique values
0 missing
red-band-flux_35numeric531 unique values
0 missing
red-band-flux_36numeric531 unique values
0 missing
red-band-flux_37numeric531 unique values
0 missing
red-band-flux_38numeric531 unique values
0 missing
red-band-flux_39numeric531 unique values
0 missing
red-band-flux_40numeric531 unique values
0 missing
red-band-flux_41numeric531 unique values
0 missing
red-band-flux_42numeric531 unique values
0 missing
red-band-flux_43numeric531 unique values
0 missing
red-band-flux_44numeric531 unique values
0 missing
red-band-flux_45numeric531 unique values
0 missing
red-band-flux_46numeric531 unique values
0 missing
red-band-flux_47numeric531 unique values
0 missing
red-band-flux_48numeric531 unique values
0 missing
red-band-flux_49numeric531 unique values
0 missing

107 properties

531
Number of instances (rows) of the dataset.
103
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.
100
Number of numeric attributes.
3
Number of nominal attributes.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
4677.61
Mean of means among attributes of the numeric type.
0.16
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.41
First quartile of kurtosis among attributes of the numeric type.
1396.74
Third quartile of standard deviation of attributes of the numeric type.
0.91
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
0.05
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0
Average mutual information between the nominal attributes and the target attribute.
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1834.51
First quartile of means among attributes of the numeric type.
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.04
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
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
1056.75
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
First quartile of mutual information between the nominal attributes and the target attribute.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.8
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
1.41
Standard deviation of the number of distinct values among attributes of the nominal type.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
3
Average number of distinct values among the attributes of the nominal type.
-1.06
First quartile of skewness among attributes of the numeric type.
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.91
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
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.97
Mean skewness among attributes of the numeric type.
820.13
First quartile of standard deviation of attributes of the numeric type.
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.04
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
0.11
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
89.64
Percentage of instances belonging to the most frequent class.
1314.82
Mean standard deviation of attributes of the numeric type.
1.83
Second quartile (Median) of entropy among attributes.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.8
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
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
476
Number of instances belonging to the most frequent class.
1.83
Minimal entropy among attributes.
4.22
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.48
Entropy of the target attribute values.
1.83
Maximum entropy among attributes.
-1.18
Minimum kurtosis among attributes of the numeric type.
3765.59
Second quartile (Median) of means among attributes of the numeric type.
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
18.02
Maximum kurtosis among attributes of the numeric type.
-9.85
Minimum of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.06
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
12541.21
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
1.43
Second quartile (Median) of skewness among attributes of the numeric type.
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
0.97
Percentage of binary attributes.
1033.12
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.85
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.
277.22
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
4
The maximum number of distinct values among attributes of the nominal type.
-1.77
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
1.83
Third quartile of entropy among attributes.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.88
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
7.93
Third quartile of kurtosis among attributes of the numeric type.
0.83
Average class difference between consecutive instances.
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.05
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
5503.17
Maximum standard deviation of attributes of the numeric type.
10.36
Percentage of instances belonging to the least frequent class.
97.09
Percentage of numeric attributes.
7359.54
Third quartile of means among attributes of the numeric type.
0.91
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
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.83
Average entropy of the attributes.
55
Number of instances belonging to the least frequent class.
2.91
Percentage of nominal attributes.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
0.04
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
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
5.8
Mean kurtosis among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.83
First quartile of entropy among attributes.
2.24
Third quartile of skewness among attributes of the numeric type.
0.8
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

7 tasks

143 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 - 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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