Heating load prediction – Cross validation

This pipeline demonstrates a typical cross validation exercise for a dataset before a model is trained to prediction the target field. The dataset is a record of various aspects of a building. The building's required heating load depends upon each of these aspects. The cross validation is to validate the model's ability to predict this heating load.

• JSON Generator
• Cross Validator (Regression)

Heating load prediction

This pipeline demonstrates training a model to predict the heating load of a building. The regression algorithm is selected based on the algorithm evaluation in the Cross Validator (Regression) Snap's example. The input dataset contains various features of the building that influence its heating load.

• JSON Generator
• Cross Validator (Regression)

Weight balance classification

This pipeline demonstrates training a model to predict whether a weighing scale is balanced. The classification algorithm is selected based on the algorithm evaluation in the Cross Validator (Classification) Snap's example. The input dataset depicts the weight on each side of the scale and the side's distance from the floor.

• CSV Generator
• Trainer (Classification)
• JSON Formatter