Hi Jim,

Thank you for your comments.

About your first comment, do you mean that I should write a small tutorial about Granular Computing to introduce it to our fellow Monks? Or do you simply mean that I should keep writing the code and ask for feedback from our community? For the former case, I could certainly start by describing what the Fuzzy C-means does and how it can be used in Granular Computing. It will take me a couple of weeks, though, because I am quite busy right now with other stuff. However, to give you a preview, I can tell you that what the Fuzzy C-Means does is to look for groups in the data (that is, it groups patterns according to their similarity. This is why, some people say that the Fuzzy C-means searches for structure in the data). For the latter case, that is what I am doing: porting my code to Perl. When I get more code written, I will certainly post it on the Monastery to ask for feedback.

About your second comment, I just posted some sample data as you suggested. It is a very simple dataset. If you want to play with it, what I suggest you do is the following:

  1. Plot the data using your favourite program. I suggest you use an XY chart. On this chart, you might notice that there are two groups of patterns: one close to (0, 0) and the other close to (12, 10)
  2. Run the code available in the lin0's scratchpad without any argument (without arguments it will search for two groups). One of the groups will have a prototype (sort of representative element) about (1.0, 0.9) while the second one will have a prototype about (11.5, 11.2)

I really was not expecting to discuss much about the code but if people are interested, I could certainly write a node describing it in more detail.

Thanks again,

lin0

In reply to Re^2: Searching for information about Granular Computing with Perl by lin0
in thread Searching for information about Granular Computing with Perl by lin0

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