Metrics
=======
Metrics are one of the most important parts of machine learning. Unlike
traditional software, in which algorithms either work or don't work,
machine learning models work in degrees. That is, there's a continuous
range of "goodness" for a model. "Metrics" are functions which measure
how well a model works. There are many different choices of metrics
depending on the type of model at hand.

Metric Utilities
----------------
Metric utility functions allow for some common manipulations such as
switching to/from one-hot representations.

.. autofunction:: deepchem.metrics.to_one_hot

.. autofunction:: deepchem.metrics.from_one_hot

Metric Shape Handling
---------------------
One of the trickiest parts of handling metrics correctly is making sure the
shapes of input weights, predictions and labels and processed correctly. This
is challenging in particular since DeepChem supports multitask, multiclass
models which means that shapes must be handled with care to prevent errors.
DeepChem maintains the following utility functions which attempt to
facilitate shape handling for you.

.. autofunction:: deepchem.metrics.normalize_weight_shape

.. autofunction:: deepchem.metrics.normalize_labels_shape

.. autofunction:: deepchem.metrics.normalize_prediction_shape

.. autofunction:: deepchem.metrics.handle_classification_mode

Metric Functions
----------------
DeepChem has a variety of different metrics which are useful for measuring model performance. A number (but not all) of these metrics are directly sourced from :code:`sklearn`.

.. autofunction:: deepchem.metrics.matthews_corrcoef

.. autofunction:: deepchem.metrics.recall_score

.. autofunction:: deepchem.metrics.r2_score

.. autofunction:: deepchem.metrics.mean_squared_error

.. autofunction:: deepchem.metrics.mean_absolute_error

.. autofunction:: deepchem.metrics.precision_score

.. autofunction:: deepchem.metrics.precision_recall_curve

.. autofunction:: deepchem.metrics.auc

.. autofunction:: deepchem.metrics.jaccard_score

.. autofunction:: deepchem.metrics.f1_score

.. autofunction:: deepchem.metrics.roc_auc_score

.. autofunction:: deepchem.metrics.accuracy_score

.. autofunction:: deepchem.metrics.balanced_accuracy_score

.. autofunction:: deepchem.metrics.top_k_accuracy_score

.. autofunction:: deepchem.metrics.pearson_r2_score

.. autofunction:: deepchem.metrics.jaccard_index

.. autofunction:: deepchem.metrics.pixel_error

.. autofunction:: deepchem.metrics.prc_auc_score

.. autofunction:: deepchem.metrics.rms_score

.. autofunction:: deepchem.metrics.mae_score

.. autofunction:: deepchem.metrics.kappa_score

.. autofunction:: deepchem.metrics.bedroc_score

.. autofunction:: deepchem.metrics.concordance_index

.. autofunction:: deepchem.metrics.genomic_metrics.get_motif_scores

.. autofunction:: deepchem.metrics.genomic_metrics.get_pssm_scores

.. autofunction:: deepchem.metrics.genomic_metrics.in_silico_mutagenesis

Metric Class
------------
The :code:`dc.metrics.Metric` class is a wrapper around metric
functions which interoperates with DeepChem :code:`dc.models.Model`.

.. autoclass:: deepchem.metrics.Metric
  :members: