Data
energy_efficiency

energy_efficiency

active ARFF CC BY 4.0 Visibility: public Uploaded 22-12-2022 by Sebastian Fischer
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Data Description This dataset looked into assessing the heating load and cooling load requirements of buildings (that is, energy efficiency) as a function of building parameters. Energy analysis is performed 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. Various settings as functions of the afore-mentioned characteristics are simulated to obtain 768 building shapes (number of observations in the dataset). Attribute Description All features describe different properties for the building. 1. *relative_compactness* 2. *surface_area* 3. *wall_area* 4. *roof_area* 5. *overall_height* 6. *orientation* 7. *glazing_area* 8. *glazing_area_distribution* 9. *heating_load* - one possible option for target feature 10. *cooling_load* - one possible option for target feature

9 features

heating_load (target)numeric587 unique values
0 missing
relative_compactnessnumeric12 unique values
0 missing
surface_areanumeric12 unique values
0 missing
wall_areanumeric7 unique values
0 missing
roof_areanumeric4 unique values
0 missing
overall_heightnumeric2 unique values
0 missing
orientationnumeric4 unique values
0 missing
glazing_areanumeric4 unique values
0 missing
glazing_area_distributionnumeric6 unique values
0 missing
cooling_load (ignore)numeric636 unique values
0 missing

19 properties

768
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
9
Number of numeric attributes.
0
Number of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
-0.75
Average class difference between consecutive instances.
0
Percentage of missing values.
0.01
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.

2 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: heating_load
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: heating_load
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