如何使用内置数据集。这将向您显示哪些文档属于哪个主题的可能性最高。
library(topicmodels)
data("AssociatedPress", package = "topicmodels")
k <- 5 # set number of topics
# generate model
lda <- LDA(AssociatedPress[1:20,], control = list(alpha = 0.1), k)
# Now we have a topic model with 20 docs and five topics
# make a data frame with topics as cols, docs as rows and
# cell values as posterior topic distribution for each document
gammaDF <- as.data.frame(lda@gamma)
names(gammaDF) <- c(1:k)
# inspect...
gammaDF
1 2 3 4 5
1 8.979807e-05 8.979807e-05 9.996408e-01 8.979807e-05 8.979807e-05
2 8.714836e-05 8.714836e-05 8.714836e-05 8.714836e-05 9.996514e-01
3 9.261396e-05 9.996295e-01 9.261396e-05 9.261396e-05 9.261396e-05
4 9.995437e-01 1.140774e-04 1.140774e-04 1.140774e-04 1.140774e-04
5 3.573528e-04 3.573528e-04 9.985706e-01 3.573528e-04 3.573528e-04
6 5.610659e-05 5.610659e-05 5.610659e-05 5.610659e-05 9.997756e-01
7 9.994345e-01 1.413820e-04 1.413820e-04 1.413820e-04 1.413820e-04
8 4.286702e-04 4.286702e-04 4.286702e-04 9.982853e-01 4.286702e-04
9 3.319338e-03 3.319338e-03 9.867226e-01 3.319338e-03 3.319338e-03
10 2.034781e-04 2.034781e-04 9.991861e-01 2.034781e-04 2.034781e-04
11 4.810342e-04 9.980759e-01 4.810342e-04 4.810342e-04 4.810342e-04
12 2.651256e-04 9.989395e-01 2.651256e-04 2.651256e-04 2.651256e-04
13 1.430945e-04 1.430945e-04 1.430945e-04 9.994276e-01 1.430945e-04
14 8.402940e-04 8.402940e-04 8.402940e-04 9.966388e-01 8.402940e-04
15 8.404830e-05 9.996638e-01 8.404830e-05 8.404830e-05 8.404830e-05
16 1.903630e-04 9.992385e-01 1.903630e-04 1.903630e-04 1.903630e-04
17 1.297372e-04 1.297372e-04 9.994811e-01 1.297372e-04 1.297372e-04
18 6.906241e-05 6.906241e-05 6.906241e-05 9.997238e-01 6.906241e-05
19 1.242780e-04 1.242780e-04 1.242780e-04 1.242780e-04 9.995029e-01
20 9.997361e-01 6.597684e-05 6.597684e-05 6.597684e-05 6.597684e-05
# Now for each doc, find just the top-ranked topic
toptopics <- as.data.frame(cbind(document = row.names(gammaDF),
topic = apply(gammaDF,1,function(x) names(gammaDF)[which(x==max(x))])))
# inspect...
toptopics
document topic
1 1 2
2 2 5
3 3 1
4 4 4
5 5 4
6 6 5
7 7 2
8 8 4
9 9 1
10 10 2
11 11 3
12 12 1
13 13 1
14 14 2
15 15 1
16 16 4
17 17 4
18 18 3
19 19 4
20 20 3
那是你想做的吗？ 此答案的提示：https : //stat.ethz.ch/pipermail/r-help/2010-August/247706.html
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