如何在R中创建聚类图? [英] How to create a cluster plot in R?

问题描述

如何在不使用 clustplot ?

我正在设法处理一些群集(使用R)和可视化(使用HTML5 Canvas).

I am trying to get to grips with some clustering (using R) and visualisation (using HTML5 Canvas).

基本上，我想创建一个

Basically, I want to create a cluster plot but instead of plotting the data, I want to get a set of 2D points or coordinates that I can pull into canvas and do something might pretty with (but I am unsure of how to do this). I would imagine that I:

1. 为整个数据集创建一个相似度矩阵(使用dist)
2. 使用kmeans或类似的东西(使用kmeans)聚集相似性矩阵
3. 使用MDS或PCA绘制结果-但是我不确定第2步和第3步的关系(cmdscale).

我已经在此处，(最后一个是最常用的).

I've checked out questions here, here and here (with the last one being of most use).

推荐答案

您的意思是这样的吗? 抱歉，但是我对HTML5 Canvas一无所知，只有R ...但是我希望对您有所帮助...

Did you mean something like this? Sorry but i know nothing about HTML5 Canvas, only R... But I hope it helps...

首先，我使用kmeans对数据进行聚类(请注意，我没有对距离矩阵进行聚类)，然后我计算距离矩阵并使用cmdscale对其进行绘制.然后，我向MDS绘图添加与kmeans标识的组相对应的颜色.加上一些不错的附加图形功能.

First I cluster the data using kmeans (note that I did not cluster the distance matrix), than I compute the distance matix and plot it using cmdscale. Then I add colors to the MDS-plot that correspond to the groups identified by kmeans. Plus some nice additional graphical features.

您可以从cmdscale创建的对象访问坐标.

You can access the coordinates from the object created by cmdscale.

### some sample data
require(vegan)
data(dune)

# kmeans
kclus <- kmeans(dune,centers= 4, iter.max=1000, nstart=10000)

# distance matrix
dune_dist <- dist(dune)

# Multidimensional scaling
cmd <- cmdscale(dune_dist)

# plot MDS, with colors by groups from kmeans
groups <- levels(factor(kclus$cluster))
ordiplot(cmd, type = "n")
cols <- c("steelblue", "darkred", "darkgreen", "pink")
for(i in seq_along(groups)){
  points(cmd[factor(kclus$cluster) == groups[i], ], col = cols[i], pch = 16)
}

# add spider and hull
ordispider(cmd, factor(kclus$cluster), label = TRUE)
ordihull(cmd, factor(kclus$cluster), lty = "dotted")

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