Table Of Contents
Table Of Contents

mxnet.metric.CompositeEvalMetric

class mxnet.metric.CompositeEvalMetric(metrics=None, name='composite', output_names=None, label_names=None)[source]

Manages multiple evaluation metrics.

Parameters
  • metrics (list of EvalMetric) – List of child metrics.

  • name (str) – Name of this metric instance for display.

  • output_names (list of str, or None) – Name of predictions that should be used when updating with update_dict. By default include all predictions.

  • label_names (list of str, or None) – Name of labels that should be used when updating with update_dict. By default include all labels.

Examples

>>> predicts = [mx.nd.array([[0.3, 0.7], [0, 1.], [0.4, 0.6]])]
>>> labels   = [mx.nd.array([0, 1, 1])]
>>> eval_metrics_1 = mx.metric.Accuracy()
>>> eval_metrics_2 = mx.metric.F1()
>>> eval_metrics = mx.metric.CompositeEvalMetric()
>>> for child_metric in [eval_metrics_1, eval_metrics_2]:
>>>     eval_metrics.add(child_metric)
>>> eval_metrics.update(labels = labels, preds = predicts)
>>> print eval_metrics.get()
(['accuracy', 'f1'], [0.6666666666666666, 0.8])
__init__(metrics=None, name='composite', output_names=None, label_names=None)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([metrics, name, output_names, …])

Initialize self.

add(metric)

Adds a child metric.

get()

Returns the current evaluation result.

get_config()

Save configurations of metric.

get_global()

Returns the current evaluation result.

get_global_name_value()

Returns zipped name and value pairs for global results.

get_metric(index)

Returns a child metric.

get_name_value()

Returns zipped name and value pairs.

reset()

Resets the internal evaluation result to initial state.

reset_local()

Resets the local portion of the internal evaluation results to initial state.

update(labels, preds)

Updates the internal evaluation result.

update_dict(labels, preds)

Update the internal evaluation with named label and pred