neuraxle.metaopt.data.reporting¶

Module-level documentation for neuraxle.metaopt.data.reporting. Here is an inheritance diagram, including dependencies to other base modules of Neuraxle:

Neuraxle’s AutoML Metric Reporting classes.¶

Classes are splitted like this for the metric analysis:

ProjectReport
ClientReport
RoundReport
TrialReport
TrialSplitReport

These AutoML reports are used to get information from the nested dataclasses, such as to create visuals.

Classes

`BaseReport`(dc)	A report contains a dataclass of the same subclass-level of itself, so as to be able to dig into the dataclass so as to observe it, such as to generate statistics and query its information.
`ClientReport`(dc)
`MetricResultsReport`(dc)
`ProjectReport`(dc)
`RootReport`(dc)
`RoundReport`(dc)
`TrialReport`(dc)
`TrialSplitReport`(dc)

neuraxle.metaopt.data.reporting._filter_df_hps(wildcarded_hps: OrderedDict[str, Any], wildcards_to_keep: List[str] = None) → OrderedDict[str, Any][source]¶: Filters the hyperparameters so as to keep only the indicated wildcards to keep. Also parses the hyperparameters to strings if not numeric.

class neuraxle.metaopt.data.reporting.BaseReport(dc: SubDataclassT)[source]¶

Bases: typing.Generic

A report contains a dataclass of the same subclass-level of itself, so as to be able to dig into the dataclass so as to observe it, such as to generate statistics and query its information. The dataclasses represent the results of an AutoML optimization round, even multiple rounds. These AutoML reports are used to get information from the nested dataclasses, such as to create visuals.