KNN用于文本分类，但train和class在R中的长度不同
你好，我正在尝试对文本进行分类，下面是代码KNN用于文本分类，但train和class在R中的长度不同,r,text-mining,knn,tf-idf,R,Text Mining,Knn,Tf Idf,你好，我正在尝试对文本进行分类，下面是代码 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$text)) inspect(dfCorpus[1:20]) #conver
df <- read.csv("D:/AS/tokpedprepro.csv")
#sampling
set.seed(123)
df <- df[sample(nrow(df)),]
df <- df[sample(nrow(df)),]
#Convert to corpus
dfCorpus <- Corpus(VectorSource(df$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)
knn.pred您的train.class
是train.class请创建一个。
[1] 20 194
dtm.test.knn <- DocumentTermMatrix(df.corpus.test, control = list(weighting =
function(x) weightTfIdf(x, normalize = FALSE)))
dim(dtm.test.knn)
[1] 17 211
knn.pred <- knn(dtm.train.knn, dtm.test.knn, train.class, k=1 )