Question

我试图在R中运行Naive Bayes，以便根据文本数据进行预测（通过构建文档术语矩阵）。

我读了几个帖子警告可能在训练和测试集中都缺少的术语，所以我决定只使用一个数据框并在之后拆分它。我使用的代码是：

data <- read.csv(file="path",header=TRUE)

########## NAIVE BAYES
library(e1071)
library(SparseM)
library(tm)

# CREATE DATA FRAME AND TRAINING AND
# TEST INCLUDING 'Text' AND 'InfoType' (columns 8 and 27)
traindata <- as.data.frame(data[13000:13999,c(8,27)])
testdata <- as.data.frame(data[14000:14999,c(8,27)])
complete <- as.data.frame(data[13000:14999,c(8,27)])

# SEPARATE TEXT VECTOR TO CREATE Source(),
# Corpus() CONSTRUCTOR FOR DOCUMENT TERM
# MATRIX TAKES Source()
completevector <- as.vector(complete$Text)

# CREATE SOURCE FOR VECTORS
completesource <- VectorSource(completevector)

# CREATE CORPUS FOR DATA
completecorpus <- Corpus(completesource)

# STEM WORDS, REMOVE STOPWORDS, TRIM WHITESPACE
completecorpus <- tm_map(completecorpus,tolower)
        completecorpus <- tm_map(completecorpus,PlainTextDocument)
        completecorpus <- tm_map(completecorpus, stemDocument)
completecorpus <- tm_map(completecorpus, removeWords,stopwords("english"))
        completecorpus <- tm_map(completecorpus,removePunctuation)
        completecorpus <- tm_map(completecorpus,removeNumbers)
        completecorpus <- tm_map(completecorpus,stripWhitespace)

# CREATE DOCUMENT TERM MATRIX
completematrix<-DocumentTermMatrix(completecorpus)
trainmatrix <- completematrix[1:1000,]
testmatrix <- completematrix[1001:2000,]

# TRAIN NAIVE BAYES MODEL USING trainmatrix DATA AND traindata$InfoType CLASS VECTOR
model <- naiveBayes(as.matrix(trainmatrix),as.factor(traindata$InfoType),laplace=1)

# PREDICTION
results <- predict(model,as.matrix(testmatrix))
conf.matrix<-table(results, testdata$InfoType,dnn=list('predicted','actual'))

conf.matrix

问题在于我得到了如此奇怪的结果：

               actual
predicted    1   2   3
         1  60 833 107
         2   0   0   0
         3   0   0   0

为什么会发生这种情况？

原始数据如下所示：

head(complete)

      Text
13000 Milkshakes, milkshakes, whats not to love? Really like the durability and weight of the cup. Something about it sure makes good milkshakes.Works beautifully with the Cuisinart smart stick.
13001 excellent. shipped on time, is excellent for protein shakes with a cuisine art mixer.  easy to clean and the mixer fits in perfectly
13002 Great cup. Simple and stainless steel great size cup for use with my cuisinart mixer.  I can do milkshakes really easy and fast. Recommended. No problems with the shipping.
13003 Wife Loves This. Stainless steel....attractive and the best part is---it won't break. We are considering purchasing another one because they are really nice.
13004 Great! Stainless steel cup is great for smoothies, milkshakes and even chopping small amounts of vegetables for salads!Wish it had a top but still love it!
13005 Great with my. Stick mixer...the plastic mixing container cracked and became unusable as a result....the only downside is you can't see if the stuff you are mixing is mixed well 

      InfoType
13000        2
13001        2
13002        2
13003        3
13004        2
13005        2

Answer 1

看来问题是TDM需要摆脱这么多的稀疏性。所以我补充道：

completematrix<-removeSparseTerms(completematrix, 0.95)

它开始工作!!

             actual
predicted   1   2   3
        1  60 511   6
        2   0  86   2
        3   0 236  99

谢谢大家的意见（谢谢Chelsey Hill !!）

朴素贝叶斯的问题

1 个答案: