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Additional metrics integrated with the keras NN library, taken directly from `Tensorflow <https://www.tensorflow.org/api_docs/python/tf/metrics/>`_

Project description

Travis CI build SonarCloud Quality SonarCloud Maintainability Codacy Maintainability Maintainability Pypi project Pypi total project downloads

Additional metrics integrated with the Keras NN library.

How do I install this package?

As usual, just download it using pip:

pip install extra_keras_metrics

Tests Coverage

Since some software handling coverages sometimes get slightly different results, here’s three of them:

Coveralls Coverage SonarCloud Coverage Code Climate Coverate

How do I use this package?

Other than by importing the single metrics from the package, we make available also sets of metrics.

Multi-class metrics

To retrieve an instance of the set of multi-class metrics you can use:

from extra_keras_metrics import get_minimal_multiclass_metrics

model = my_keras_model()
model.compile(
    optimizer="nadam",
    loss="categorical_crossentropy",
    metrics=get_minimal_multiclass_metrics()
)

Binary metrics

To retrieve an instance of the set of binary-class metrics you can use:

from extra_keras_metrics import get_standard_binary_metrics

model = my_keras_model()
model.compile(
    optimizer="nadam",
    loss="binary_crossentropy",
    metrics=get_standard_binary_metrics()
)

All the binary metrics

We have implemented all sorts of binary metrics, including some relatively more obscure ones. If you want ALL the binary metrics we implemented you can use the following method:

from extra_keras_metrics import get_complete_binary_metrics

model = my_keras_model()
model.compile(
    optimizer="nadam",
    loss="binary_crossentropy",
    metrics=get_complete_binary_metrics()
)

Extras

I’ve created also another couple packages you might enjoy this other one, called extra_keras_utils that contains some commonly used code for Keras projects and plot_keras_history <https://github.com/LucaCappelletti94/plot_keras_history> which automatically plots a Keras training history.

Project details


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