R 中用于文本分类的 SVM

Question

我正在使用 SVM 对我的文本进行分类，但我实际上并没有得到结果，而是通过数值概率得到的。

Dataframe（1:20 训练集，21:50 测试集）

更新：

     ou <- structure(list(text = structure(c(1L, 6L, 1L, 1L, 8L, 13L, 24L, 
5L, 11L, 12L, 33L, 36L, 20L, 25L, 4L, 19L, 9L, 29L, 22L, 3L, 
8L, 8L, 8L, 2L, 8L, 27L, 30L, 3L, 14L, 35L, 3L, 34L, 23L, 31L, 
22L, 6L, 6L, 7L, 17L, 3L, 8L, 32L, 18L, 15L, 21L, 26L, 3L, 16L, 
10L, 28L), .Label = c("access, access, access, access", "character(0)", 
"report", "report, access", "report, access, access", "report, access, access, access", 
"report, access, access, access, access, access, access", "report, access, access, access, access, access, access, access", 
"report, access, access, access, access, access, access, report", 
"report, access, access, access, access, access, report", "report, access, access, access, report", 
"report, access, access, access, report, access", "report, access, access, report, access, access, access, access, access, access", 
"report, data", "report, data, data", "report, data, data, data", 
"report, data, data, data, data", "report, data, data, data, data, data", 
"report, data, data, data, report, report, data, access,access", 
"report, data, data, report", "report, data, report", "report, report", 
"report, report, access, access, access", "report, report, access, access, report, report, report, report, report, report, data, data, report, access, report, report", 
"report, report, access, report, report, report, report, report, data, data, report, access, report, report", 
"report, report, access, report, report, report, report, report, report, data, data, report, access, report, report", 
"report, report, data", "report, report, data, report", "report, report, report, data, report, report, data, data, report, data, data", 
"report, report, report, report", "report, report, report, report, data, report, report, data, report, data, report", 
"report, report, report, report, report, data, report, data, data", 
"report, report, report, report, report, report, report", "report, report, report, report, report, report, report, access, access, access", 
"report, report, report, report, report, report, report, report, data, data, report, access, report, report", 
"report, report, report, report, report, report, report, report, report, report, data, report, report, report, report, report, report, report,report"
), class = "factor"), value = structure(c(2L, 2L, 2L, 2L, 2L, 
2L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 2L, 3L, 2L, 3L, 3L, 3L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("", 
"Access", "Report/Data"), class = "factor")), .Names = c("text", 
"value"), class = "data.frame", row.names = c(NA, -50L))

使用代码：

        library(RTextTools)

        doc_matrix <- create_matrix(ou$text, language="english", removeNumbers=TRUE, stemWords=TRUE, removeSparseTerms=.998)

        #container <- create_container(doc_matrix, ou$text, trainSize=1:20, testSize=21:50, virgin=FALSE)
        container <- create_container(doc_matrix, as.numeric(factor(ou$text)), trainSize=1:20, testSize=21:50, virgin=FALSE)

        #Training models
        SVM <- train_model(container,"SVM")
        MAXENT <- train_model(container,"MAXENT")
        BAGGING <- train_model(container,"BAGGING")
        TREE <- train_model(container,"TREE")

        #Classify data using trained models
        SVM_CLASSIFY <- classify_model(container, SVM)
        MAXENT_CLASSIFY <- classify_model(container, MAXENT)
        BAGGING_CLASSIFY <- classify_model(container, BAGGING)

        #Analytics

        analytics <- create_analytics(container,SVM_CLASSIFY)

        models <- train_models(container, algorithms=c("MAXENT","SVM"))
        results <- classify_models(container, models)
        analytics <- create_analytics(container, results)
        summary(analytics)
        SVM <- cross_validate(container, 5, "SVM")
        write.csv(analytics@document_summary, "DocumentSummary.csv")

预期结果：

          text                                                          value
     21 report, access, access, access, access, access, access, access       Access
     22 report, access, access, access, access, access, access, access       Access
     23 report, access, access, access, access, access, access, access       Access
     24 character(0)                                                          NA
     25 report, access, access, access, access, access, access, access       Access
     26 report, report, data                                             Report/Data
     27 report, report, report, report                                   Report/Data
     28 report                                                          Report/Data
     29 report, data                                                    Report/Data
     30 report, report, report, report, report, report, report, report,
         data, data, report, access, report, report                      Report/Data

结果概率为：

>   MAXENTROPY_LABEL    MAXENTROPY_PROB SVM_LABEL   SVM_PROB    MANUAL_CODE CONSENSUS_CODE  CONSENSUS_AGREE CONSENSUS_INCORRECT PROBABILITY_CODE    PROBABILITY_INCORRECT
> 1 8   0.999999066 22  0.070090645 8   8   1   0   8   0
> 2 8   0.999999066 22  0.070090645 8   8   1   0   8   0
> 3 8   0.999999066 22  0.070090645 8   8   1   0   8   0
> 4 1   0.055555556 12  0.071384112 2   12  1   1   12  1
> 5 8   0.999999066 22  0.070090645 8   8   1   0   8   0
> 6 25  1   12  0.074126949 27  25  1   1   25  1
> 7 33  0.627904676 13  0.068572857 30  33  1   1   33  1
> 8 33  0.406792176 12  0.074592181 3   33  1   1   33  1
> 9 20  1   12  0.074507793 14  20  1   1   20  1

编辑 1：我怎样才能实现 标签名称 而不是 SVM 标签编号。

Answer 1

我平时做的是

ou <- cbind(ou$text, results)

并打印标签：

ou$value <- "NONE"
ou$value[results$SVM_LABEL=="1"]  <- "Access"
ou$value[results$SVM_LABEL=="-1"] <- "Report/Data"
ou

（假设你在训练模型时使用了1和-1）

我知道它有点原始，但它很清晰并且工作正常

R 中用于文本分类的 SVM

SVM for text classification in R

r

svm

text-classification

data-science

使用代码：

预期结果：