Categorize iris flowers using k-means clustering with ML.NET

This tutorial illustrates how to use ML.NET to build a clustering model for the iris flower data set.

In this tutorial, you learn how to:

• Understand the problem
• Select the appropriate machine learning task
• Prepare the data
• Load and transform the data
• Choose a learning algorithm
• Train the model
• Use the model for predictions

Prerequisites

• Visual Studio 2017 15.6 or laterwith the “.NET Core cross-platform development” workload installed.

Understand the problem

This problem is about dividing the set of iris flowers in different groups based on the flower features. Those features are the length and width of a sepal and the length and width of a petal. For this tutorial, assume that the type of each flower is unknown. You want to learn the structure of a data set from the features and predict how a data instance fits this structure.

Select the appropriate machine learning task

As you don’t know to…