Industrial Internet Application Development

Unsupervised learning

In unsupervised learning, there is no labeled data for modeling. Instead, it will use various characteristics for grouping the data and forming a cluster of related data. It can also be used for dimensionality reduction in the context of feature extraction and identifying related features. In the IIoT, unsupervised learning provides an opportunity to identify and analyze new outcomes and related patterns. It also comes in especially handy for filtering the dependent variables. As IIoT is a very complex environment, it requires a larger effort in identifying the related features.