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Recommendations on analysing and testing for biases in datasets

Virtual
Unique Identifier: c7049c9f-e33c-433e-8557-fa0a544e703b

Service Description

Providing expertise and recommendations on analysing biases in the dataset or between datasets that could influence the performance of the algorithm. Differences could, for example, be caused by measurement devices or the operator.

Method Description: For unknown biases can be tested with, for example, clustering algorithms or layer-wise relevance propagation for supervised learning.

Method reference:

Offerings: Data (FAIRness, preprocessing, standardization, best practices, etc.)
Provider Logo

Provider & Contact

Provider Organisation Friedrich-Alexander-Universitaet Erlangen-Nuernberg (FAU)
Provider Country Germany
Published Email bjoern.eskofier@fau.de
Billing: per hour
Full Price €120 EUR
Reduced Price €No discount can be provided
Pricing Detail

The final price will be determined in the contract between the service provider and the applicant.​

Operational Details

Service Inputs Dataset/Documentation about the data collection procedure (e.g. sensory output and study protocols)
Service Outputs Analysis Report highlighting potential biases/limitations of the dataset for use in AI applications
Certification Support None
Service Standards None

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