Hi guys, I'm very new to J (about 6-7 hours experience), I'm coding a bunch of
useful algos for clustering, optimisation and stats to give J a proper go: this
is my first. I (think) I've coded the k-mediods PAM algo as described here:
https://en.wikipedia.org/wiki/K-medoids
I'm trying to tune my intuition as to what this code should look like when
written properly. i.e. in canonical form. I'd be grateful for your feedback.
I've enclosed the code below which is basically the kM_step and kM functions:
the rest is testing code. If you run it it'll generate some data, cluster it
and plot it for you.
NB. UPDATE MEDIODS FROM DATA.
kM_step=: 4 : 0
d=. (x { "1 y)
s=. ([@> (i. <./) each (;/ d )) { x
idx=: I. & (= & s)
d=. { "1 ({ & y)
w=. (i. <./) & (+/%#) & d
; ((w { [) & idx) each x
)
NB. ITERATE UPDATE STEP TO CONVERGENCE.
choose=: 4 : '({~ x ? #) ,y'
kM=: 4 : '(kM_step & y) ^:_ x choose (i. #y)'
NB. CALCULATE PAIRWISE EUCLIDEAN DISTANCE MATRIX.
edist=: 3 : 0
x=. +/ |: y^2
a=. (,.x) +/ .+ (,:x)
b=. y +/ .* (|: y)
a - (2*b)
)
NB. TESTING: GENERATE DATA, FIT & PLOT.
load 'plot'
data=: ?(50 2$0)
data=: data,3+(3*?(50 2$0))
data=: data,5+(4*?(50 2$0))
D=: edist data
M=: (3 kM D) { data
pd 'reset'
pd 'type dot'
pd 'pensize 3.1'
pd 'color gray'
pd ;/ |: data
pd 'show'
pd 'color red'
pd 'pensize 4'
pd ;/ |: M
M
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