Data
auction_verification

auction_verification

active ARFF CC BY 4.0 Visibility: public Uploaded 22-12-2022 by Sebastian Fischer
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  • Machine Learning Physical Sciences study_353
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Data Description This dataset was created to verify properties of an Simultaneous Multi-Round (SMR) auction model. The creators of the dataset use BPMN to model the design of the German 4G spectrum auction to sell 800 MHz band. The auction has four bidders and six products. A random budget is assigned from the range [1, 100] to each bidder for each product. A reserve price of 3 is also defined for all products. Further, each bidder has an individual capacity. Each instance in the dataset represents a simulation of an auction. Attribute Description 1. *process.b1.capacity* - an integer in [0, 3], denoting the current capacities of the bidders 2. *process.b2.capacity* - an integer in [0, 3], denoting the current capacities of the bidders 3. *process.b3.capacity* - an integer in [0, 3], denoting the current capacities of the bidders 4. *process.b4.capacity* - an integer in [0, 3], denoting the current capacities of the bidders 5. *property.price* - an integer in [59, 90], denoting the price that is currently verified for the property.product 6. *property.product* - an integer in [1, 6], denoting the currently verified product 7. *property.winner* - an integer in [1, 4], denoting the bidder that is currently verified as winner for the property.product with the property.price. This feature is empty for iterations where the price is not clear yet. 8. *verification.result* - a boolean denoting if current property is satisfied in the underlying Petri Net or not, ignored column 9. *verification.time* - a positive integer, denoting the time (in ms) for verifying the current property against the underlying Petri Net, target feature

8 features

verification.time (target)numeric2039 unique values
0 missing
process.b1.capacitynumeric3 unique values
0 missing
process.b2.capacitynumeric4 unique values
0 missing
process.b3.capacitynumeric2 unique values
0 missing
process.b4.capacitynumeric2 unique values
0 missing
property.pricenumeric32 unique values
0 missing
property.productnominal6 unique values
0 missing
property.winnernominal5 unique values
0 missing
verification.result (ignore)nominal2 unique values
0 missing

19 properties

2043
Number of instances (rows) of the dataset.
8
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.
6
Number of numeric attributes.
2
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.
-8534.01
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
75
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
25
Percentage of nominal attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: verification.time
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