# Examples¶

Here you can find various examples of using FAT-Forensics.

Note

Please note that all of the examples using the fatf.utils.models.models.KNN model class may be slow as our implementation of the k-nearest neighbours algorithm is in pure Python, hence is rather slow.

# Accountability Examples¶

Here you can find various examples of how to use FAT-Forensics to evaluate accountability – security, safety, robustness and privacy – of data sets, machine learning models and their predictions.

# Fairness Examples¶

Here you can find various examples of how to use FAT-Forensics to evaluate and mitigate a range of fairness aspects of data sets, machine learning models and their predictions.

# Transparency Examples¶

Here you can find various examples of how to use FAT-Forensics to explain and interpret data sets, machine learning models and their predictions.

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