I describe here an interesting and intuitive clustering algorithm (that can be used for data reduction as well) offering several advantages, over traditional classifiers: More robust against outliers and erroneous data Executing much faster Generalizing well known algorithms You don't need to know K-NN to understand this article -- but click here if you want to learn more about it. You don't ne…
Most Popular Content on DSC
To not miss this type of content in the future, subscribe to our newsletter.
Other popular resources
Most popular articles