What is Machine Learning Classification?

Machine learning classification is an AutoClassifier feature that enables the ability to apply tags without writing tagging rules, based on the training data provided for each taxonomy node.

Using the training data provided for each taxonomy node, machine learning algorithms are trained to classify new items or documents based on what the algorithms learned. 

Example

To train the AutoClassifier Machine Learning algorithm, the AutoClassifier administrator provides AutoClassifier a set of documents (approx. 100) that are representative of a single taxonomy node:

1. For example, 100 HR documents from your HR department for your HR taxonomy node is fed into the AutoClassifier machine learning model.
2. After the AutoClassifier machine learning model is trained, new documents or items processed by AutoClassifier are automatically evaluated by the machine learning model.
3. The AutoClassifier Machine Learning algorithm determines:
   1. Which of the trained taxonomy nodes apply to the recently processed new documents or items
   2. Classifies (tags) the documents or items accordingly