问题
I am using the regular method to do a Hierarchical Clustering project.
mydata.dtm <- TermDocumentMatrix(mydata.corpus)
mydata.dtm2 <- removeSparseTerms(mydata.dtm, sparse=0.98)
mydata.df <- as.data.frame(inspect(mydata.dtm2))
mydata.df.scale <- scale(mydata.df)
d <- dist(mydata.df.scale, method = "euclidean") # distance matrix
fit <- hclust(d, method="ward")
groups <- cutree(fit, k=10)
groups
congestion cough ear eye fever flu fluzonenon medicare painpressure physical pink ppd pressure
1 2 3 4 5 6 5 5 5 7 4 8 5
rash screening shot sinus sore sports symptoms throat uti
5 5 6 1 9 7 5 9 10
And I what I want is to put the group number back to the new column in the original data.
I've looked at approximate string matching within single list - r
Because the df here is a document matrix so what I got after df <- t(data.frame(mydata.df.scale,cutree(hc,k=10)))
is a matrix like
df[1:5,1:5]
congestion cough ear eye fever
[1,] 0 0 0 0 0
[2,] 0 0 0 0 0
[3,] 0 0 0 0 0
[4,] 0 0 0 1 0
[5,] 0 0 0 0 0
Since eye has the group number 3 then I want add the number 3 to the new column in 4th row.
note that in this case a single document can be mapped to two items in the same group.
df[23,17:21]
sinus sore sports symptoms throat
0 1 0 0 1
回答1:
Instead of put back the number directly I use the 0-1 matrix:
label_back <-t(data.frame(mydata.df,cutree(fit,k=10)))
row.names(label_back) <- NULL
#label_back<-label_back[1:(nrow(label_back)-1),]# the last line is the sum
groups.df<-as.data.frame(groups)
groups.df$label<-rownames(groups.df)
for (i in 1:length((colnames(label_back)))){
ind<-which(colnames(label_back)[i]==groups.df$label) # match names and return index
label_back[,i]=groups.df$groups[ind]*label_back[,i] # time the 0-1 with the #group number
}
find the max value in each row because there are more than 1 value in some rows.
data_group<-rep(0,nrow(data)
for (i in 1:nrow(data)){
data_group[i]<-max(unique(label_back[i,]))
}
data$group<-data_group
I am looking for more elegant way.
来源:https://stackoverflow.com/questions/28378113/match-and-add-the-cluster-number-to-the-original-data