Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...

Abstract: This paper presents a new method that combines deep k-means clustering with granule mining approaches to utilise contextual information for improving outlier detection and classification.

The desktop application provides the best experience with zero environment setup required. Simply download and run.

The purpose of this repository is to provide a few sample prompts used in order to create a simple Python GUI for the Linux desktop project. I created this repository and wrote these prompts on March ...