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Plans for lattice reduction? #7
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Thanks for the feedback (happy if this is useful to anyone).
I think I am not familiar. Do you mean this method? https://github.com/simplerick/nn_fca/blob/master/local/fca.py#L244-L249 Not sure if it uses the stability currently: https://github.com/simplerick/nn_fca/blob/master/local/fca.py#L198-L203 Would this be for removing (omitting) arbitrary nodes from the graph when rendering for visualization or rather for keeping the reduced graph structure for further usage? Both |
I must admit I'm a novice, all I know about reduction/clarification is from this unit of the Coursera course on FCA. The basic idea, as I understand it, is that you set a cutoff point for stability, support or probability of concepts and eliminate them from the line graph to make it less noisy. I'm mainly interested in this for the purposes of visualizing overall lattice structure, so mutating the data structures probably wouldn't be necessary. |
Thanks for the link. IIUC both clarification and reduction are applied to the context (rather than its lattice) creating a new clarified/reduced context. So the Adding e.g. When it comes to removing nodes from the lattice graph (only for visualization or creating a new graph), I am wondering about the exact semantics: Say we have |
I think I need to do some more reading in this area. Since my original question was based on a misunderstanding, I'm going to close this issue. I'll come back to it when I have a better understanding. |
Many thanks for your work on this! After playing around with this for a while I inevitably wound up with some messy lattices, so I was wondering whether you have any plans to include simple lattice reduction techniques based on stability, support and the like in
concepts
.I came across this repository with an MIT-licensed Python implementation of lattice reduction, and if it's of interest I could try to integrate that in this library.
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