Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Need help with evaluating model! #286

Open
aryan1107 opened this issue Mar 23, 2022 · 0 comments
Open

Need help with evaluating model! #286

aryan1107 opened this issue Mar 23, 2022 · 0 comments

Comments

@aryan1107
Copy link

Hi I am new to this, I am successfully able to train and evaluate my model, however now I am wondering how do I recompute the same metrics and performance gap using fairness indicators.

My model is something like this:

def model_func():   
    model = tf.keras.models.Sequential([
        keras.layers.Dense(units = 14, input_dim=14, activation='relu'),
        keras.layers.Dense(units = 28, activation='relu'),
        keras.layers.Dense(units = 1,  activation='sigmoid')
        ])

    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])

    return model

Then I train model and test it on test data-set.

# Geting my trained model
model = model_func()

# Training my model
train = model.fit(X_train, y_train, epochs=50, batch_size=10, verbose = 1)

Now how do I recompute the same metrics and performance gap using fairness indicators?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant