October 2017
Beginner to intermediate
572 pages
26h 1m
English
book
Machine Learning with R Cookbook - Second Edition
by AshishSingh Bhatia, Yu-Wei, Chiu (David Chiu)
Content preview from Machine Learning with R Cookbook - Second Edition
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How to do it...
Perform the following steps to compute the silhouette information:
- Use kmeans to generate a k-means object, km:
> set.seed(22)
> km = kmeans(customer, 4)
- You can then compute the silhouette information:
> kms = silhouette(km$cluster,dist(customer))
> summary(kms)
Output
Silhouette of 60 units in 4 clusters from silhouette.default(x = km$cluster, dist = dist(customer)) :
Cluster sizes and average silhouette widths:
8 11 16 25
0.5464597 0.4080823 0.3794910 0.5164434
Individual silhouette widths:
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.1931 0.4030 0.4890 0.4641 0.5422 0.6333
- Next, you can plot the silhouette information:
> plot(kms)
The silhouette plot of the k-means clustering result
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.