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

This is demo code implementing a semi-supervised system to evaluate our method for semi-supervised learning of neural networks, proposed in [1].. It implements a pipeline for loading a database (MNIST ...

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 ...

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 ...