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CPMP-2015-runtime-regression

CPMP-2015-runtime-regression

active ARFF Publicly available Visibility: public Uploaded 19-06-2019 by Mia Rhodes
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source: An Algorithm Selection Benchmark for the Container Pre-Marshalling Problem (CPMP) authors: K. Tierney and Y. Malitsky (features) / K. Tierney and D. Pacino and S. Voss (algorithms) translator in coseal format: K. Tierney This is an extension of the 2013 premarshalling dataset that includes more features and a set of test instances. There are three sets of features: feature_values.arff contains the full set of features from iteration 2 of our latent feature analysis (LFA) process (see paper) feature_values_itr1.arff contains only the features after iteration 1 of LFA feature_values_orig.arff containers the features used in PREMARHSALLING-ASTAR-2013 We also provide test data with an identical naming scheme (see _test). The features for the pre-marshalling problem are all extremely easy and fast to compute, thus the feature_costs.arff file has been omitted, as it would be time 0 for every feature (regardless of using original, iteration 1 or iteration 2 features). The feature computation code is available at https://bitbucket.org/eusorpb/cpmp-as Note: previously the scenario was called PREMARSHALLING-ASTAR-2015. To save same space, we renamed the scenario.

24 features

runtime (target)numeric1161 unique values
0 missing
top.good.maxnumeric31 unique values
0 missing
row_id (row identifier)string2108 unique values
0 missing
algorithmnominal4 unique values
0 missing
pct.bottom.pct.on.topnumeric22 unique values
0 missing
cont.empty.grt.estacknumeric62 unique values
0 missing
avg.l1.top.left.lg.groupnumeric218 unique values
0 missing
tier.weighted.groupsnumeric522 unique values
0 missing
left.densitynumeric215 unique values
0 missing
bflbnumeric49 unique values
0 missing
overstowage.pctnumeric69 unique values
0 missing
top.good.stdevnumeric484 unique values
0 missing
top.good.meannumeric281 unique values
0 missing
stacksnumeric10 unique values
0 missing
top.good.minnumeric8 unique values
0 missing
group.same.stdevnumeric139 unique values
0 missing
group.same.meannumeric13 unique values
0 missing
group.same.maxnumeric12 unique values
0 missing
group.same.minnumeric2 unique values
0 missing
overstowing.2cont.stack.pctnumeric34 unique values
0 missing
overstowing.stack.pctnumeric22 unique values
0 missing
empty.stack.pctnumeric15 unique values
0 missing
container.densitynumeric7 unique values
0 missing
stack.tier.rationumeric17 unique values
0 missing
tiersnumeric4 unique values
0 missing
Show all 24 features

62 properties

NumberOfInstances
2108
Number of instances (rows) of the dataset.
NumberOfFeatures
24
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
23
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
95.83
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
4.17
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.46
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
0.15
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.14
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.38
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0.85
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.6
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.5
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.22
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
5.87
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.79
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
2.69
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
-997.24
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
54.54
Mean of means among attributes of the numeric type.
ClassEntropy
Entropy of the target attribute values.
Dimensionality
0.01
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
6.07
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
1164.93
Maximum of means among attributes of the numeric type.
MaxMutualInformation
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
1.81
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
1582.56
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-0.03
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
4
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.48
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
70.54
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-2
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.07
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
4
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1.68
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.05
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
Show all 62 properties

8 tasks

Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
Clustering on CPMP-2015-runtime-regression
0 runs - estimation_procedure: 50 times Clustering
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