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energy-efficiency

energy-efficiency

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Author: Angeliki Xifara, Athanasios Tsanas Source: UCI Please cite: Source: The dataset was created by Angeliki Xifara (angxifara @ gmail.com, Civil/Structural Engineer) and was processed by Athanasios Tsanas (tsanasthanasis @ gmail.com, Oxford Centre for Industrial and Applied Mathematics, University of Oxford, UK). Data Set Information: We perform energy analysis using 12 different building shapes simulated in Ecotect. The buildings differ with respect to the glazing area, the glazing area distribution, and the orientation, amongst other parameters. We simulate various settings as functions of the afore-mentioned characteristics to obtain 768 building shapes. The dataset comprises 768 samples and 8 features, aiming to predict two real valued responses. It can also be used as a multi-class classification problem if the response is rounded to the nearest integer. Attribute Information: The dataset contains eight attributes (or features, denoted by X1...X8) and two responses (or outcomes, denoted by y1 and y2). The aim is to use the eight features to predict each of the two responses. Specifically: X1 Relative Compactness X2 Surface Area X3 Wall Area X4 Roof Area X5 Overall Height X6 Orientation X7 Glazing Area X8 Glazing Area Distribution y1 Heating Load y2 Cooling Load

10 features

y1 (target)nominal37 unique values
0 missing
V1numeric12 unique values
0 missing
V2numeric12 unique values
0 missing
V3numeric7 unique values
0 missing
V4numeric4 unique values
0 missing
V5numeric2 unique values
0 missing
V6numeric4 unique values
0 missing
V7numeric4 unique values
0 missing
V8numeric6 unique values
0 missing
y2nominal38 unique values
0 missing
Show all 10 features

107 properties

NumberOfInstances
768
Number of instances (rows) of the dataset.
NumberOfFeatures
10
Number of attributes (columns) of the dataset.
NumberOfClasses
37
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
8
Number of numeric attributes.
NumberOfSymbolicFeatures
2
Number of nominal attributes.
AutoCorrelation
0.5
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
0.42
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
0.56
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
0.42
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
0.56
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
0.42
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
0.56
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
4.67
Entropy of the target attribute values.
DecisionStumpAUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.85
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.01
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
1.64
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.39
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.39
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.39
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.59
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
9.64
Percentage of instances belonging to the most frequent class.
MajorityClassSize
74
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
4.7
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
0.12
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
671.71
Maximum of means among attributes of the numeric type.
MaxMutualInformation
2.85
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
38
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
0.53
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
88.09
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
4.7
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-1.16
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
147.42
Mean of means among attributes of the numeric type.
MeanMutualInformation
2.85
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
0.65
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
37.5
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.07
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
22.69
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
4.7
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-2.01
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.23
Minimum of means among attributes of the numeric type.
MinMutualInformation
2.85
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
37
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.16
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.11
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
0.13
Percentage of instances belonging to the least frequent class.
MinorityClassSize
1
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.52
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
80
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
20
Percentage of nominal attributes.
Quartile1AttributeEntropy
4.7
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.67
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
1.28
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
2.85
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.12
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.38
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
4.7
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-1.24
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
4.38
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
2.85
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
-0.03
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
1.65
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
4.7
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
-0.79
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
283.03
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
2.85
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.37
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
44.78
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.33
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.33
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.33
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0.71
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.42
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.56
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

13 tasks

Supervised Classification on energy-efficiency
52 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: y1
Supervised Classification on energy-efficiency
51 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: y2
Clustering on energy-efficiency
0 runs
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Clustering on energy-efficiency
0 runs - estimation_procedure: 50 times Clustering
Define a new task