Faster clustering of complex data with the generalised harmonic topographic mapping(G-HaToM)
In this paper we explain the Generalised Harmonic topographic Map (G-HaToM), an extension of the Harmonic Topographic map [3] and [4]. This algorithm extends the mapping from data space to latent space using the pth power of the L2 distance, where the second power is the former version of the topographic mapping, HaToM. This generalization allows the mapping of more difficult data, reducing at the same time the computational cost of the mapping for the data already clustered by the original HaToM.