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DEE

DEE

active ARFF Public Domain (CC0) Visibility: public Uploaded 19-04-2020 by Rafael Gomes Mantovani
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Daily electric energy dataset The dee problem involves predicting the daily average price of TkWhe electricity energy in Spain. The data set contains real values from 2003 about the daily consumption in Spain of energy from hydroelectric, nuclear electric, carbon, fuel, natural gas and other special sources of energy. Missing values. No ### Attributes 1. Hydroelectric real[27881.8,206035.0] 2. Nuclear real[114760.0,187105.0] 3. Coal real[33537.0,234833.0] 4. Fuel real[0.0,67986.5] 5. Gas real[0.0,84452.2] 6. Special real[5307.0,16357.0] 7. Consume real[0.765853,5.11875]

7 features

Consume (target)numeric365 unique values
0 missing
Hydroelectricnumeric365 unique values
0 missing
Nuclearnumeric363 unique values
0 missing
Coalnumeric364 unique values
0 missing
Fuelnumeric343 unique values
0 missing
Gasnumeric359 unique values
0 missing
Specialnumeric354 unique values
0 missing

19 properties

365
Number of instances (rows) of the dataset.
7
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.
7
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of instances having missing values.
0.42
Average class difference between consecutive instances.
0
Percentage of missing values.
0.02
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.
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.

8 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: Consume
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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