问题描述
在聚类分析中，可以通过单链接方法轻松识别数据集的异常值.现在，我想自动删除异常值.我的想法是删除超过指定距离值的数据.这是我的代码，其中包含mtcars的示例数据:
in the cluster analysis the outliers of a dataset can be easily identified by the single-linkage method. Now I would like to remove the outliers automatically. My idea is to remove the data which exceed a specified distance value. Here is my code with the example data of mtcars:
library(cluster)
library(dendextend)
cluster<-agnes(mtcars,stand=FALSE,method="single")
dend = as.dendrogram(cluster)
在图解中，您可以看到生成的树状图.最后4辆车("Duster 360"，"Camaro Z28"，"Ford Pantera L"，"Maserati Bora")被识别为异常值，因此我想删除(数据集mtcars的)孔行.如何自动完成?例如.删除高度超过70的行?我尝试了很多方法来消除离群值，但它们似乎不适用于我的数据.
In the Plot you can see the resulting dendrogram. The last 4 cars ("Duster 360", "Camaro Z28", "Ford Pantera L", "Maserati Bora") are identified outliers so I would like to remove their hole rows(of the dataset mtcars). How can I do it automatically? E.g. remove the rows which height is above 70? I've tried a lot of possibilities to remove outliers but they did not seem to be applicable to my data.
非常感谢！
推荐答案
尝试一下:
# your code
library(cluster)
cluster<-agnes(mtcars,stand=FALSE,method="single")
dend = as.dendrogram(cluster)
plot(dend)
#new code
hclu <- as.hclust(cluster) # convert to list that cutree() understands
groupindexes <- cutree(hclu, h = 70) # cut at height 70 - creates 3 groups/branches
mtcars[groupindexes != 1,] # "outliers" - not in group 1 but in groups 2 and 3
mtcars[groupindexes == 1,] # all but the 4 "outliers"
结果1-异常值":
mpg cyl disp hp drat wt qsec vs am gear carb
Duster 360 14.3 8 360 245 3.21 3.57 15.84 0 0 3 4
Camaro Z28 13.3 8 350 245 3.73 3.84 15.41 0 0 3 4
Ford Pantera L 15.8 8 351 264 4.22 3.17 14.50 0 1 5 4
Maserati Bora 15.0 8 301 335 3.54 3.57 14.60 0 1 5 8
结果2:
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
(....and ~30 other rows ....)
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