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shuttle-landing-control

shuttle-landing-control

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# Space Shuttle Autolanding Domain NASA: Mr. Roger Burke's autolander design team ##### Past Usage: (several, it appears) Example: Michie,D. (1988). The Fifth Generation's Unbridged Gap. In Rolf Herken (Ed.) The Universal Turing Machine: A Half-Century Survey, 466-489, Oxford University Press. ##### Relevant Information: This is a tiny database. Michie reports that Burke's group used RULEMASTER to generate comprehendable rules for determining the conditions under which an autolanding would be preferable to manual control of the spacecraft. ##### Number of Instances: 15 ##### Number of Attributes: 7 (including the class attribute) ##### Attribute Information: 1. Class: noauto, auto -- that is, advise using manual/automatic control 2. STABILITY: stab, xstab 3. ERROR: XL, LX, MM, SS 4. SIGN: pp, nn 5. WIND: head, tail 6. MAGNITUDE: Low, Medium, Strong, OutOfRange 7. VISIBILITY: yes, no ##### Missing Attribute Values: -- none -- but several "don't care" values: (denoted by "*") Attribute Number: Number of Don't Care Values: 2: 2 3: 3 4: 8 5: 8 6: 5 7: 0 ##### Class Distribution: 1. Use noauto control: 6 2. Use automatic control: 9% Information about the dataset\ CLASSTYPE: nominal\ CLASSINDEX: first

7 features

Class (target)nominal2 unique values
0 missing
STABILITYnominal2 unique values
2 missing
ERRORnominal4 unique values
3 missing
SIGNnominal2 unique values
8 missing
WINDnominal2 unique values
8 missing
MAGNITUDEnominal4 unique values
5 missing
VISIBILITYnominal2 unique values
0 missing
Show all 7 features

107 properties

NumberOfInstances
15
Number of instances (rows) of the dataset.
NumberOfFeatures
7
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
26
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
9
Number of instances with at least one value missing.
NumberOfNumericFeatures
0
Number of numeric attributes.
NumberOfSymbolicFeatures
7
Number of nominal attributes.
AutoCorrelation
0.71
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.57
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
CfsSubsetEval_DecisionStumpErrRate
0.47
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
CfsSubsetEval_DecisionStumpKappa
0.05
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
CfsSubsetEval_NaiveBayesAUC
0.67
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
CfsSubsetEval_NaiveBayesErrRate
0.4
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
CfsSubsetEval_NaiveBayesKappa
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
CfsSubsetEval_kNN1NAUC
0.67
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
CfsSubsetEval_kNN1NErrRate
0.4
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
CfsSubsetEval_kNN1NKappa
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
ClassEntropy
0.97
Entropy of the target attribute values.
DecisionStumpAUC
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.47
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
6.7
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.47
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.47
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.47
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
60
Percentage of instances belonging to the most frequent class.
MajorityClassSize
9
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.75
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.35
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
4
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
0.89
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.14
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
5.11
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2.57
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.35
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
Minimum of means among attributes of the numeric type.
MinMutualInformation
0.03
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
40
Percentage of instances belonging to the least frequent class.
MinorityClassSize
6
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
5
Number of binary attributes.
PercentageOfBinaryFeatures
71.43
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
60
Percentage of instances having missing values.
PercentageOfMissingValues
24.76
Percentage of missing values.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
100
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.35
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0.04
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
0.6
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.09
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
1.69
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.28
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.47
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.47
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.47
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
-0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
-0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
-0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0.98
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.49
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
-0.25
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

19 tasks

Supervised Classification on shuttle-landing-control
458 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on shuttle-landing-control
350 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: VISIBILITY
Supervised Classification on shuttle-landing-control
213 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: VISIBILITY
Supervised Classification on shuttle-landing-control
209 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on shuttle-landing-control
32 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Learning Curve on shuttle-landing-control
179 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: VISIBILITY
Supervised Data Stream Classification on shuttle-landing-control
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: VISIBILITY
Supervised Data Stream Classification on shuttle-landing-control
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
Clustering on shuttle-landing-control
0 runs
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
Clustering on shuttle-landing-control
0 runs - estimation_procedure: 50 times Clustering
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