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Make experiments in categorization projects

Overview

Once the resources have been set up and the documents have been annotated, you can start experiments that consist of creating the categorization ML model.

An experiment process is based on a:

  • Test library
  • Model

The test library, or test set, consists of an annotated document set parsed by the model in order to check it.

The model parses the test library in order to give the analysis results.

Annotate provides the following available model types for categorization projects:

The first model creates a Machine Learning model, while the second one creates a categorization model based on an expert.ai Studio CPK of an imported project.

model based on an expert.ai Studio CPK of an imported project.

To start an experiment:

  1. In the upper bar, select Start an experiment to pre-annotate documents .

  2. In the Start an experiment dialog:

    2.1. Enter the experiment name in Name or leave empty for automatic assignment.

    2.2. Select the library you need in the Test library drop-down menu.

    2.3. Select one of the available engine types:

    • Auto-ML Categorization

    Or:

    • Studio

  3. Select Start to start the experiment or Next if you selected Studio.

The experiment progress window is displayed during the engine process.

To terminate the process before its end, select Delete experiment.

The process consists of six sequential stages:

  1. Initialization
  2. Model generation preparation
  3. Model generation
  4. Document analysis preparation
  5. Document analysis
  6. Experiment wrap-up

Once the process is completed, the analytics are displayed in the Experiments tab, Statistics sub-tab where it is possible to interpret the results.

Studio engine procedure

  1. Select the model in Model selection, then select Next to go on.
  2. Check the remap in Remapper, then select Next to go on.
  3. Check the summary, then select Start.