RE: [R] Interpreting knn Results
Maybe you should show your colleague how to access help pages in R? Right
in ?knn, it says:
prob: If this is true, the proportion of the votes for the winning
class are returned as attribute 'prob'.
so 1.0 mean all three NNs are of the `winning'; i.e., predicted, class, and
0.7 means 2 out of the 3 NNs are of the winning class, etc.
Andy
From: Ko-Kang Kevin Wang
Hi,
[I'm posting this on behalf of a colleague -- as I don't know
knn myself...]
How to interpret the knn() results?
Tried the example codes in the documentation:
data(iris3)
train - rbind(iris3[1:25,,1], iris3[1:25,,2], iris3[1:25,,3])
test - rbind(iris3[26:50,,1], iris3[26:50,,2], iris3[26:50,,3])
cl - factor(c(rep(s,25), rep(c,25), rep(v,25)))
knn(train, test, cl, k = 3, prob=TRUE)
attributes(.Last.value)
and got:
$levels
[1] c s v
$class
[1] factor
$prob
[1] 1.000 1.000 1.000 1.000 1.000 1.000
[7] 1.000 1.000 1.000 1.000 1.000 1.000
[13] 1.000 1.000 1.000 1.000 1.000 1.000
[19] 1.000 1.000 1.000 1.000 1.000 1.000
[25] 1.000 1.000 1.000 0.667 1.000 1.000
[31] 1.000 1.000 1.000 0.667 1.000 1.000
[37] 1.000 1.000 1.000 1.000 1.000 1.000
[43] 1.000 1.000 1.000 1.000 1.000 1.000
[49] 1.000 1.000 1.000 0.667 0.750 1.000
[55] 1.000 1.000 1.000 1.000 0.500 1.000
[61] 1.000 1.000 1.000 0.667 1.000 1.000
[67] 1.000 1.000 1.000 1.000 1.000 0.667
[73] 1.000 1.000 0.667
What do the prob mean?
Thanks,
Kevin
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RE: [R] Interpreting knn Results
Hi, -Original Message- From: Liaw, Andy [mailto:[EMAIL PROTECTED] Maybe you should show your colleague how to access help pages in R? Right in ?knn, it says: prob: If this is true, the proportion of the votes for the winning class are returned as attribute 'prob'. so 1.0 mean all three NNs are of the `winning'; i.e., predicted, class, and 0.7 means 2 out of the 3 NNs are of the winning class, etc. Whoops sorry, I guess I should've known that *_*. She lost access to her email due to a technical problem and I was running to a tutorial so didn't have time to think. After my tutorial I looked at the results with her and figured it out*_* Thanks, Kevin __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Interpreting knn Results
Hi, [I'm posting this on behalf of a colleague -- as I don't know knn myself...] How to interpret the knn() results? Tried the example codes in the documentation: data(iris3) train - rbind(iris3[1:25,,1], iris3[1:25,,2], iris3[1:25,,3]) test - rbind(iris3[26:50,,1], iris3[26:50,,2], iris3[26:50,,3]) cl - factor(c(rep(s,25), rep(c,25), rep(v,25))) knn(train, test, cl, k = 3, prob=TRUE) attributes(.Last.value) and got: $levels [1] c s v $class [1] factor $prob [1] 1.000 1.000 1.000 1.000 1.000 1.000 [7] 1.000 1.000 1.000 1.000 1.000 1.000 [13] 1.000 1.000 1.000 1.000 1.000 1.000 [19] 1.000 1.000 1.000 1.000 1.000 1.000 [25] 1.000 1.000 1.000 0.667 1.000 1.000 [31] 1.000 1.000 1.000 0.667 1.000 1.000 [37] 1.000 1.000 1.000 1.000 1.000 1.000 [43] 1.000 1.000 1.000 1.000 1.000 1.000 [49] 1.000 1.000 1.000 0.667 0.750 1.000 [55] 1.000 1.000 1.000 1.000 0.500 1.000 [61] 1.000 1.000 1.000 0.667 1.000 1.000 [67] 1.000 1.000 1.000 1.000 1.000 0.667 [73] 1.000 1.000 0.667 What do the prob mean? Thanks, Kevin __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
