fixout 0.1.28

Algorithmic inspection for trustworthy ML models

Algorithmic inspection for trustworthy ML models

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Getting started

How to start analysing a simple model (let's say you have trained a binary classifier on the German Credit Data):

from fixout.artifact import FixOutArtifact
from fixout.runner import FixOutRunner

fxo = FixOutRunner("Credit Risk Assessment (German Credit)") 

# Indicate the sensitive features
sensitive_features = ["foreignworker","telephone","statussex"] 

# Create a FixOut Artifact with your model and data
fxa = FixOutArtifact(model=model,
                      training_data=(X_train,y_train), 
                      testing_data=[(X_test,y_test,"Testing")],
                      features_name=features_name,
                      sensitive_features=sensitive_features,
                      dictionary=dic)

Then run the inspection

fxo.run(fxa, show=True)

Finally, you can access the generated dashboard at http://localhost:5000 ;)

You should be able to see an interface similar to the following