To train and improve the performance Threshold and Configurations can be specified for all three NLP engines – FM, KG and ML. You can access these settings under Natural Language > Training > Thresholds & Configurations. The settings for ML engine is discussed in detail in the following sections.
The Bots Platform ver 6.3 upgraded its Machine Learning (ML) model to v3. This includes a host of improvements and also allows developers to fine tune the model using parameters to suit business requirement. The developers can change parameters like stopword usage, synonym usage, thresholds, and n-grams, as well as opt between Deep Neural Network or Conditional Random Field-based algorithm for the Named-Entity Recognition (NER) model.
All new bots that are created use the new ML model by default. Developers can upgrade the ML model for old bots or downgrade the model for the bots using the new model.
Upgrading the ML Model
If you are using a previous model of ML in the bots platform, you can upgrade it as follows:
- Open the bot for which you want to upgrade the ML model and go to Natural Language > Advanced Settings.
- Expand Machine Learning. Under ML Upgrade section, click the Upgrade Now button. It opens a confirmation window.
- Click Upgrade and Train. You can see new customizable options under the Machine Learning section.
You can also downgrade the ML model for new or upgraded bots from here by clicking Switch to older version. However, note that the older version of the ML model will be deprecated soon. So, we strongly recommend staying on the latest version to receive continued support and future enhancements.
Note: If a bot is exported using the older model (V2) and imported as a new bot, it continues to be in V2 model until you upgrade it.
Configuring the Machine Learning Parameters
The Bots Platform provides language-wise defaults for the following parameters related to the ML performance of your bot. You can customize them to suit your particular needs.
This setting is Disabled by default. Enable this option if you would like to consider intent synonyms in building the ML model.
This setting is Disabled by default. Enable this option if you would like to remove the stop words in the training utterances in building the ML model.
ML Definitive Score
Configure the threshold score for definite matches, can be set to a value between 80-100%.
n-gram Sequence Length
n-gram is the contiguous sequence of words to be used from training sentences to train the model. For example, if Generate sales forecast report is the user utterance and if n-gram is set to 2, then Generate sales, Sales forecast, and Forecast report are used in training the model.
The minimum n-gram limit is 1 by default. You can set the maximum limit up to 4.
Define the minimum ML score to qualify an intent as a probable match. Learn more about ML Scoring.
Choose the NER model to be used for entity detection.
Enable to replace entity values present in the training utterances with the corresponding entity placeholders in the training model.