Introduction
In Machine Learning, Multiclass Classifiers use a collection of input features to assign classifications involving 3 or more label possibilities. LunchBoxML implements Multiclass Classification in Grasshopper using Microsoft’s ML.NET library.
Examples
Plan Type Selector
This example implements Multiclass Classification to select among 100 possible floor plans types based on features including overall dimensions and space quantities.
Following selection of a plan type, the Grasshopper definition loads the applicable floor plan from a directory for visualization.
The example incudes two definitions:
- Trainer: a definition for training the Multiclass Classification model on features and labels for the plan library.
- Tester: a definition for using the saved training model to select plan types based on user-defined feature criteria.
Note: Users will need to set the Grasshopper file and directory path inputs to reflect their local file locations.
