# Extra Keras Metrics

Additional metrics integrated with the TensorFlow and Keras Neural Network libraries.

## How do I install this package?

As usual, just download it using pip:

`pip install extra_keras_metrics`

## 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()
)
```

### Sparse multi-class metrics

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

```
from extra_keras_metrics import get_sparse_multiclass_metrics
model = my_keras_model()
model.compile(
optimizer="nadam",
loss="sparse_categorical_crossentropy",
metrics=get_sparse_multiclass_metrics()
)
```

Note that for now this only includes the categorial accuracy, since it is the only one provided out-of-the-box by Tensorflow. We will be implementing more metrics ourselves.

### 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 which automatically plots a Keras training history.