【发布时间】:2020-04-29 07:38:33
【问题描述】:
您好,我正在尝试对文本进行分类,这是代码
df <- read.csv("D:/AS/tokpedprepro.csv")
#sampling
set.seed(123)
df <- df[sample(nrow(df)),]
df <- df[sample(nrow(df)),]
#Convert to corpus
dfCorpus <- Corpus(VectorSource(df$text))
inspect(dfCorpus[1:20])
#convert DTM
dtm <- DocumentTermMatrix(dfCorpus)
inspect(dtm[1:4, 3:7])
#Data Partition
df.train <- df[1:20,]
df.test <- df[21:37,]
dtm.train <- dtm[1:20,]
dtm.test <- dtm[21:37,]
df.Corpus.train <- dfCorpus[1:20]
df.corpus.test <- dfCorpus[21:37]
train.class <- df$data.class
#TFIDF
dtm.train.knn <- DocumentTermMatrix(df.Corpus.train, control = list(weighting =
function(x) weightTfIdf(x, normalize = FALSE)))
dim(dtm.train.knn)
维度是
[1] 20 194
dtm.test.knn <- DocumentTermMatrix(df.corpus.test, control = list(weighting =
function(x) weightTfIdf(x, normalize = FALSE)))
dim(dtm.test.knn)
维度是
[1] 17 211
然后
knn.pred <- knn(dtm.train.knn, dtm.test.knn, train.class, k=1 )
但是错误 'train' 和 'class' 有不同的长度
我该怎么办? 谢谢
【问题讨论】:
-
请创建一个reproducible example。
标签: r text-mining knn tf-idf