Industrial Internet Application Development

Training a model

The first step in building a model is to train a model with a dataset. To make it simple to understand the steps here, I am referring to a linear regression technique. Typically, the linear regression technique (Y = mX + c) will be trained with a sample dataset. The dataset can be divided into training and testing datasets to train the linear equation to come up with the best possibility for m and c. By using the training dataset, the model can be fitted with various data points from the training dataset that will end up, for example, something like Y = 4X + 10.