Google Cloud Ai Platform V1 Client - Class ThresholdConfig (0.32.0)

Version 0.32.0

• 1.13.1 (latest)
• 1.13.0
• 1.12.0
• 1.11.0
• 1.10.0
• 1.9.0
• 1.8.0
• 1.7.0
• 1.6.0
• 1.5.0
• 1.4.0
• 1.3.0
• 1.2.0
• 1.1.0
• 1.0.0
• 0.39.0
• 0.38.0
• 0.37.1
• 0.32.0
• 0.31.0
• 0.30.0
• 0.29.0
• 0.28.0
• 0.27.0
• 0.26.2
• 0.25.0
• 0.24.0
• 0.23.0
• 0.22.0
• 0.21.0
• 0.20.0
• 0.19.0
• 0.18.0
• 0.17.0
• 0.16.0
• 0.15.0
• 0.13.0
• 0.12.0
• 0.11.1
• 0.10.0

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ThresholdConfig.

The config for feature monitoring threshold.

Generated from protobuf message google.cloud.aiplatform.v1.ThresholdConfig

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name	Description
data	array Optional. Data for populating the Message object.
↳ value	float Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

getValue

Specify a threshold value that can trigger the alert.

If this threshold config is for feature distribution distance:

1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

Returns
Type	Description
float

hasValue

setValue

Specify a threshold value that can trigger the alert.

If this threshold config is for feature distribution distance:

1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

Parameter
Name	Description
var	float

Returns
Type	Description
$this

getThreshold

Returns
Type	Description
string