This page is not created by, affiliated with, or supported by Slack Technologies, Inc.
2019-12-08
Channels
- # adventofcode (60)
- # announcements (3)
- # babashka (31)
- # beginners (5)
- # boot (1)
- # calva (13)
- # cider (9)
- # clj-kondo (1)
- # clojure (135)
- # clojure-italy (18)
- # clojure-nl (18)
- # clojure-spec (21)
- # clojure-uk (11)
- # clojuredesign-podcast (1)
- # clojurescript (47)
- # core-async (14)
- # emacs (7)
- # euroclojure (4)
- # fulcro (3)
- # graalvm (19)
- # off-topic (22)
- # reagent (29)
- # shadow-cljs (25)
- # vim (3)
Every Christmas we go see the RSNO and a choir do The Snowman at Caird Hall in Dundee. It is a fun night
I know there's some data scientists in this room. How would I go about getting a fuzzy clustering algorithm to hand/easily. I just want to play around with some basic stuff. I think FCM is what I want, I have some vague memberships/relationships between points, and I'd like to do analysis to see if the occurrences are simply outliers and should be ignored, or if they're recurring/relevant and therefore should be grouped together. I don't know how many clusters I want to end up with, so fuzzy seems the most appropriate of the options?