Module training_config

Amber API Server

Boon Logic Amber API server

OpenAPI spec version: 2.0.0

Generated by: https://github.com/swagger-api/swagger-codegen.git

Classes

class TrainingConfig (history_window=None, buffering_samples=None, learning_max_samples=None, learning_max_clusters=None, learning_rate_numerator=None, learning_rate_denominator=None)

NOTE: This class is auto generated by the swagger code generator program.

Do not edit the class manually.

TrainingConfig - a model defined in Swagger

Instance variables

var buffering_samples

Gets the buffering_samples of this TrainingConfig.

Number of data vectors to collect during Buffering. These samples are used as data for Autotuning.

:return: The buffering_samples of this TrainingConfig. :rtype: int

var history_window

Gets the history_window of this TrainingConfig.

Number of past inferences to take into account when computing warningLevel at a given moment.

:return: The history_window of this TrainingConfig. :rtype: int

var learning_max_clusters

Gets the learning_max_clusters of this TrainingConfig.

Maximum number of clusters before model transitions from Learning to Monitoring.

:return: The learning_max_clusters of this TrainingConfig. :rtype: int

var learning_max_samples

Gets the learning_max_samples of this TrainingConfig.

Maximum number of vectors to process during Learning before transitioning to Monitoring.

:return: The learning_max_samples of this TrainingConfig. :rtype: int

var learning_rate_denominator

Gets the learning_rate_denominator of this TrainingConfig.

See learningRateNumerator.

:return: The learning_rate_denominator of this TrainingConfig. :rtype: int

var learning_rate_numerator

Gets the learning_rate_numerator of this TrainingConfig.

Switch to Monitoring if there were fewer than learningRateNumerator new clusters in the last learningRateDenominator inferences.

:return: The learning_rate_numerator of this TrainingConfig. :rtype: int

Methods

def to_dict(self)

Returns the model properties as a dict

def to_str(self)

Returns the string representation of the model