Classes Based

Collect and save images that match a class from a classifier prediction for use in improving your model.

Tip

Review the Active Learning page for more information about how to use active learning.

This strategy is available for the following model types:

classification

Configuration¶

name: user-defined name of the strategy - must be non-empty and unique within all strategies defined in a single configuration (required)
type: with value classes_based is used to identify close to threshold sampling strategy (required)
selected_class_names: list of class names to consider during sampling - (required)
probability: fraction of datapoints that matches sampling criteria that will be persisted. It is meant to be float value in range [0.0, 1.0] (required)
tags: list of tags (each contains 1-64 characters from range a-z, A-Z, 0-9, and -_:/.[]<>{}@) (optional)

Example¶

Here is an example of a configuration manifest for the close to threshold sampling strategy:

{
  "name": "underrepresented_classes",
  "type": "classes_based",
  "selected_class_names": ["cat"],
  "probability": 1.0,
  "tags": ["hard-classes"],
  "limits": [
    { "type": "minutely", "value": 10 },
    { "type": "hourly", "value": 100 },
    { "type": "daily", "value": 1000 }
  ]
}

Learn how to configure active learning for your model.