In most of the machine learning models, we will talk about how we start with classification. Classification is a form of supervised learning where the data is used to pick a name, value, or category. For example, using a neural network to scan images to find pictures of a shoe. In this field, there are two variants of classification:
- Binomial: If you are picking between one of two categories (coffee, tea)
- Multi-class: If there are more than two options
We use the Stanford linear classifier tool to help understand the concept of hyperplanes (http://vision.stanford.edu/teaching/cs231n-demos/linear-classify/). The following diagram shows a trained learning system's attempts to find the best hyperplane to divide colored balls. ...
