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Concrete_Data

active ARFF Publicly available Visibility: public Uploaded 22-01-2016 by unknown
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Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients. These ingredients include cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, and fine aggregate.

9 features

Cement (component 1)(kg in a m^3 mixture)	numeric	278 unique values 0 missing
Blast Furnace Slag (component 2)(kg in a m^3 mixture)	numeric	185 unique values 0 missing
Fly Ash (component 3)(kg in a m^3 mixture)	numeric	156 unique values 0 missing
Water (component 4)(kg in a m^3 mixture)	numeric	195 unique values 0 missing
Superplasticizer (component 5)(kg in a m^3 mixture)	numeric	111 unique values 0 missing
Coarse Aggregate (component 6)(kg in a m^3 mixture)	numeric	284 unique values 0 missing
Fine Aggregate (component 7)(kg in a m^3 mixture)	numeric	302 unique values 0 missing
Age (day)	numeric	14 unique values 0 missing
Concrete compressive strength(MPa. megapascals)	numeric	845 unique values 0 missing

Show all 9 features

107 properties

NumberOfInstances

1030

Number of instances (rows) of the dataset.

NumberOfFeatures

Number of attributes (columns) of the dataset.

NumberOfClasses

Number of distinct values of the target attribute (if it is nominal).

NumberOfMissingValues

Number of missing values in the dataset.

NumberOfInstancesWithMissingValues

Number of instances with at least one value missing.

NumberOfNumericFeatures

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

AutoCorrelation

Average class difference between consecutive instances.

CfsSubsetEval_DecisionStumpAUC

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

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

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

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

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

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

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

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

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

Entropy of the target attribute values.

DecisionStumpAUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

DecisionStumpErrRate

Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump

DecisionStumpKappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump

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.

J48.00001.AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.00001.ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.00001.Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001

J48.0001.AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.0001.ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.0001.Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

J48.001.AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001

J48.001.ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001

J48.001.Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001

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

12.17

Maximum kurtosis among attributes of the numeric type.

MaxMeansOfNumericAtts

972.92

Maximum of means among attributes of the numeric type.

MaxMutualInformation

Maximum mutual information between the nominal attributes and the target attribute.

MaxNominalAttDistinctValues

The maximum number of distinct values among attributes of the nominal type.

MaxSkewnessOfNumericAtts

3.27

Maximum skewness among attributes of the numeric type.

MaxStdDevOfNumericAtts

104.51

Maximum standard deviation of attributes of the numeric type.

MeanAttributeEntropy

Average entropy of the attributes.

MeanKurtosisOfNumericAtts

1.15

Mean kurtosis among attributes of the numeric type.

MeanMeansOfNumericAtts

269.44

Mean of means among attributes of the numeric type.

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

Average number of distinct values among the attributes of the nominal type.

MeanSkewnessOfNumericAtts

0.69

Mean skewness among attributes of the numeric type.

MeanStdDevOfNumericAtts

57.77

Mean standard deviation of attributes of the numeric type.

MinAttributeEntropy

Minimal entropy among attributes.

MinKurtosisOfNumericAtts

-1.33

Minimum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

6.2

Minimum of means among attributes of the numeric type.

MinMutualInformation

Minimal mutual information between the nominal attributes and the target attribute.

MinNominalAttDistinctValues

The minimal number of distinct values among attributes of the nominal type.

MinSkewnessOfNumericAtts

-0.25

Minimum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

5.97

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.

NaiveBayesAUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NaiveBayesErrRate

Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NaiveBayesKappa

Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes

NumberOfBinaryFeatures

Number of binary attributes.

PercentageOfBinaryFeatures

Percentage of binary attributes.

PercentageOfInstancesWithMissingValues

Percentage of instances having missing values.

PercentageOfMissingValues

Percentage of missing values.

PercentageOfNumericFeatures

100

Percentage of numeric attributes.

PercentageOfSymbolicFeatures

Percentage of nominal attributes.

Quartile1AttributeEntropy

First quartile of entropy among attributes.

Quartile1KurtosisOfNumericAtts

-0.56

First quartile of kurtosis among attributes of the numeric type.

Quartile1MeansOfNumericAtts

40.74

First quartile of means among attributes of the numeric type.

Quartile1MutualInformation

First quartile of mutual information between the nominal attributes and the target attribute.

Quartile1SkewnessOfNumericAtts

0.02

First quartile of skewness among attributes of the numeric type.

Quartile1StdDevOfNumericAtts

19.03

First quartile of standard deviation of attributes of the numeric type.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

Quartile2KurtosisOfNumericAtts

-0.31

Second quartile (Median) of kurtosis among attributes of the numeric type.

Quartile2MeansOfNumericAtts

73.9

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

0.51

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

Third quartile of entropy among attributes.

Quartile3KurtosisOfNumericAtts

0.77

Third quartile of kurtosis among attributes of the numeric type.

Quartile3MeansOfNumericAtts

527.37

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

0.85

Third quartile of skewness among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

83.23

Third quartile of standard deviation of attributes of the numeric type.

REPTreeDepth1AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth1ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth1Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1

REPTreeDepth2AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth2ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth2Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2

REPTreeDepth3AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3

REPTreeDepth3ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3

REPTreeDepth3Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3

RandomTreeDepth1AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth1ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth1Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

RandomTreeDepth2AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth2ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth2Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

RandomTreeDepth3AUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

RandomTreeDepth3ErrRate

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

RandomTreeDepth3Kappa

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

StdvNominalAttDistinctValues

Standard deviation of the number of distinct values among attributes of the nominal type.

kNN1NAUC

Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk

kNN1NErrRate

Error rate achieved by the landmarker weka.classifiers.lazy.IBk

kNN1NKappa

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

Show all 107 properties

13 tasks

Supervised Regression on Concrete_Data

3 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: root_mean_squared_error - target_feature: Concrete compressive strength(MPa. megapascals)

Supervised Regression on Concrete_Data

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Concrete compressive strength(MPa. megapascals)

Clustering on Concrete_Data

0 runs

Clustering on Concrete_Data