ClassifierMetric¶
Inheritance Diagram
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class
ashpy.metrics.classifier.
ClassifierMetric
(metric, model_selection_operator=None, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.2.0/docs/source/log', processing_predictions=None)[source]¶ Bases:
ashpy.metrics.metric.Metric
Wrap a metric using argmax to extract predictions out of a classifier’s output.
Methods
__init__
(metric[, model_selection_operator, …])Initialize the Metric.
update_state
(context)Update the internal state of the metric, using the information from the context object.
Attributes
best_folder
Retrieve the folder used to save the best model when doing model selection.
best_model_sel_file
Retrieve the path to JSON file containing the measured performance of the best model.
logdir
Retrieve the log directory.
metric
Retrieve the
tf.keras.metrics.Metric
object.model_selection_operator
Retrieve the operator used for model selection.
name
Retrieve the metric name.
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__init__
(metric, model_selection_operator=None, logdir='/home/docs/checkouts/readthedocs.org/user_builds/ashpy/checkouts/v0.2.0/docs/source/log', processing_predictions=None)[source]¶ Initialize the Metric.
- Parameters
metric (
tf.keras.metrics.Metric
) – The Keras Metric to use with the classifier (e.g.: Accuracy()).model_selection_operator (
typing.Callable
) –The operation that will be used when model_selection is triggered to compare the metrics, used by the update_state. Any
typing.Callable
behaving like anoperator
is accepted.Note
Model selection is done ONLY if an model_selection_operator is specified here.
logdir (str) – Path to the log dir, defaults to a log folder in the current directory.
processing_predictions (
typing.Dict
) – A dict in the form of {“fn”: tf.argmax, “kwargs”: {“axis”: -1}} with a function “fn” to be used for predictions processing purposes and its “kwargs” as its keyword-arguments. Defaults to {“fn”: tf.argmax, “kwargs”: {“axis”: -1}}.
- Return type
None
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