Giuseppe Vettigli
Giuseppe Vettigli
Hi there, Minisom doesn't implement any classification mechanisms, hence I'm not sure how you computed the f score. There's one example in the documentation that can help you but the...
Hyperparameters tuning has already been covered here https://github.com/JustGlowing/minisom/issues/101
Hi there, the method get_weights returns a matrix with the weight vector for each coordinate in the map. Once your som is trained they should be arranged in a good...
It's an interesting approach but I'm not sure the mean is reflective of the topology. Try with a 2D dataset first to have a feel. For higher dimensional data you...
It looks very good. I might add this example in the library if I managed to generalize the code that plots the lines.
hi @mariajmolina This example shows how to visualize the lattice in a 3D chart without using sammons to reduce the dimensionality: https://colab.research.google.com/drive/1UnJKG3i0mvUiOJB2UPxaSDygwlcv34w0?usp=sharing
hi Adam, You get that warning because the current implementation of the `bubble` and `triangle` functions doesn't center the values properly when sigma is even. If `sigma=1` only the winning...
My bad, I meant when sigma is even. I also corrected my first answer for future readers.
hi @omerbt small changes in sigma can have big impacts on the results of training even when sigma is kept below 1. It all depends on the size of the...
Yes, sigma is the spread of the neighbourhood function. The bigger sigma, the more bigger the neighbourhood that will be affected by the training step.