smclarify

We have hosted the application smclarify in order to run this application in our online workstations with Wine or directly.

Quick description about smclarify:

Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models. A facet is column or feature that will be used to measure bias against. A facet can have value(s) that designates that sample as "sensitive". Bias detection and mitigation for datasets and models. The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function that returns a bias metric. A bias metric is a numerical value indicating the level of bias detected as determined by a particular bias measure. A collection of bias metrics for a given dataset or a combination of a dataset and model.

Features:

• Install the package from PIP
• Bias measure
• Bias report
• Bias metric
• You can see examples on running the Bias metrics on the notebooks in the examples folder
• Mitigation for datasets and models

Programming Language: Python.
Categories: