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autoMpg

autoMpg

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Felicia West
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  • binarized mythbusting_1 study_1 study_123 study_15 study_20 study_41
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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').

8 features

binaryClass (target)nominal2 unique values
0 missing
cylindersnominal5 unique values
0 missing
displacementnumeric82 unique values
0 missing
horsepowernumeric93 unique values
6 missing
weightnumeric351 unique values
0 missing
accelerationnumeric95 unique values
0 missing
modelnominal13 unique values
0 missing
originnominal3 unique values
0 missing
Show all 8 features

107 properties

NumberOfInstances
398
Number of instances (rows) of the dataset.
NumberOfFeatures
8
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
6
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
6
Number of instances with at least one value missing.
NumberOfNumericFeatures
4
Number of numeric attributes.
NumberOfSymbolicFeatures
4
Number of nominal attributes.
AutoCorrelation
0.83
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.9
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
0.13
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
0.75
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
0.9
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
0.13
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
0.75
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
0.9
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
0.13
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
0.75
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
1
Entropy of the target attribute values.
DecisionStumpAUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.02
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
2.98
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
52.51
Percentage of instances belonging to the most frequent class.
MajorityClassSize
209
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
3.69
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
0.7
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
2970.42
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.54
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
13
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
1.09
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
846.84
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
2.2
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-0.1
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
820.97
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.33
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
5.58
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
5.75
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.65
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
248.09
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
1.33
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.79
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
15.57
Minimum of means among attributes of the numeric type.
MinMutualInformation
0.22
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
0.28
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
2.76
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
47.49
Percentage of instances belonging to the least frequent class.
MinorityClassSize
189
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
12.5
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
1.51
Percentage of instances having missing values.
PercentageOfMissingValues
0.19
Percentage of missing values.
PercentageOfNumericFeatures
50
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
50
Percentage of nominal attributes.
Quartile1AttributeEntropy
1.33
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.78
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
37.79
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0.22
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
0.34
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
11.69
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.59
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.16
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
148.95
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.24
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.63
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
71.38
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
3.69
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.63
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
2276.17
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.54
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
1
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
661.2
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
4.99
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

15 tasks

Supervised Classification on autoMpg
504 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on autoMpg
201 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on autoMpg
0 runs - estimation_procedure: 33% Holdout set - target_feature: binaryClass
Supervised Data Stream Classification on autoMpg
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
Clustering on autoMpg
0 runs
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
Clustering on autoMpg
0 runs - estimation_procedure: 50 times Clustering
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