Industrial Internet Application Development

Supervised learning

In supervised learning, the model is built by learning from the data observed. The observed data is well known and created in the past by giving inputs and generated output, so that the data can be used and fitted with a function to build a model by splitting the data into training and testing. Typically, in IIoT, predicting the anomalies, classifying the type, analyzing the size of the ore, and forecasting the time series data can be done using supervised learning. Classification and regression are among the supervised learning methodologies for building the models.