An Artificial Life Approach for Semi-supervised Learning [chapter]

Lutz Herrmann, Alfred Ultsch
2008 Studies in Classification, Data Analysis, and Knowledge Organization  
An approach for the integration of supervising information into unsupervised clustering is presented (semi supervised learning). The underlying unsupervised clustering algorithm is based on swarm technologies from the field of Artificial Life systems. Its basic elements are autonomous agents called Databots. Their unsupervised movement patterns correspond to structural features of a high dimensional data set. Supervising information can be easily incorporated in such a system through the
more » ... ntation of special movement strategies. These strategies realize given constraints or cluster informations. The system has been tested on fundamental clustering problems. It outperforms constrained k-means.
doi:10.1007/978-3-540-78246-9_17 fatcat:ahjtfx6edvffbicawjhhu73l44