Hi All

Hope you are doing fine in these strange times. I got a problem with bias_variance_decomp while using it for tf.keras.models.Model. The problem was coming from /mlxtend/evaluate/bias_variance_decomp.py L110. First of all, for some reason my model can't pass if estimator.__class__.__name__ in ['Sequential', 'Functional'] so it goes through else at L108 where code takes pred = estimator.fit(...).predict(...) but estimator.fit is just history object apparently and it doesn't have predict functionality, so I patched it as follows

        else:
            estimator.fit(X_boot, y_boot, **fit_params)#.predict(X_test)
            pred = estimator.predict(X_test).reshape(1, -1)

but wanted to run by you to see if it might create any problem in the future or if I'm missing anything.

Python version 3.6
Tensorflow v2.1 (Keras within)

Thanks
Cheers
Jack