Unlabelled data is more suitable for tasks that require high flexibility, creativity, and generality, such as clustering, dimensionality reduction, or generation.

Design decision: the clustering algorithm is designed to train on labelled data. However, I've written it in such a way that it's easy to change to unlabelled data -- I considered making it modular ...

The pink and green labels obviously cluster in different parts of the space. FYI, the entire algorithm is an unsupervised one. Labels are just used to color and visually test the results. If you don't ...

Graclus is a fast clustering tool that computes the clusters from unlabelled data using graph representations. The input data to be clustered is first encoded into a graph with its information in the ...

With the rapid increase of high-dimensional data mixed with labelled and unlabelled samples, the semi-supervised feature selection technique has received much attention in recent years. However, most ...

Clustering of high-dimensional data is a challenging task, since the usual distance measures in high-dimensional space cannot reflect how clusters are partitioned. In this work, by assuming there are ...