AI Studio Step 4: Validation
Contents
AI Studio Step 4: Validation#
Profiles: Model Creator, Data Scientist
As a model creator or data scientist, the fourth step in AI Studio is validation.
This page explains the validation functionality within AI Studio.
Overview#
In the Validation section you can see the performance of your model tested on the ground truth.
The model gets tested only on unseen data, due to the k-fold validation approach.
Usage#
All models within a project are listed in the Validation Dashboard as shown below:
Note: The Accuracy of the model is shown in the last column after the training process is finished.
Tip: To see the detailed validation of a model, click Validate.
The performance of a model is shown in the Validate Model screen. In addition to common performance metrics and the confusion matrix, there is a detailed view of text extracts that have been classified correctly or incorrectly, as shown below:
In case the performance of the trained model stays below expectations, it can be helpful to try one of the following tips:
Try another template.
Check which examples got miss classified and add more similar example.
Add more examples to the ground truth.
Try to build a successful proximity rule model first and use the bulk labeling feature to expand your ground truth set.