Machine Learning models require training before they can be used to perform tasks.

Training Machine Learning Models

Training a model in Tiki is a one-step process. The model must have been created and fully configured with a data source tracker to be used for training. Tiki will check if the set source tracker contain any items (samples), and will halt the training process if there are none, and display an error message.

To train a model, go to the List Models page and click on the Actions button of the model, then select Train.

Model will be trained using items from source tracker and a success message will be shown on completion.

Testing the Model

Testing a model in Tiki is the same as training except that only a sample of the model is created and it is not saved. Call it dry training.

This feature is useful in checking to know if model can learn with the linked source tracker. To test a model, open the model's action menu and click on Test.

Related links

• Machine Learning
• Preparing Machine Learning Dataset
• Creating Machine Learning Models
• Configuring Machine Learning Models
• Using Machine Learning Models