Personality: Personality

In pingqingsheng/Robot0001: What the package does (short line)

Usage

Personality()

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function () 
{
    cat("\n")
    cat("Do you want a sketch of the candidate Master?", "\n")
    response <- readline(prompt = "Yes/No:")
    if (response == "Yes") {
        centerText(paste("Personality descripting....."))
        cat("\n")
        filename <- list.files(patter = "(Trump_[0-9])+|(Clinton_[0-9])+")
        temp <- read.csv(filename[1], header = TRUE, nrows = 1)
        for (name in filename) {
            temp <- rbind(temp, read.csv(name, header = TRUE))
        }
        temp <- temp[-1, ]
        temp$Speaker <- as.character(temp$Speaker)
        temp$Speaker[grep("Clinton+", temp$Speaker)] <- "Clinton"
        temp$Speaker[grep("Trump+", temp$Speaker)] <- "Trump"
        temp <- temp[temp$Speaker %in% c("Clinton", "Trump"), 
            ]
        temp$Text <- as.character(temp$Text)
        temp$Text <- iconv(temp$Text, to = "utf8")
        traincorpus <- Corpus(VectorSource(temp$Text))
        traincorpus <- tm_map(traincorpus, stripWhitespace)
        traincorpus <- tm_map(traincorpus, tolower)
        traincorpus <- tm_map(traincorpus, removeNumbers)
        trainmatrix <- t(TermDocumentMatrix(traincorpus))
        trainmatrix <- removeSparseTerms(trainmatrix, 0.99)
        M_bayes <- naiveBayes(as.matrix(trainmatrix), as.factor(temp$Speaker), 
            laplace = 1)
        fit <- predict(M_bayes, as.matrix(trainmatrix))
        table(fit, temp$Speaker)
        cat("Model Accuracy", "\n")
        (Tab_ac <- table(fit, temp$Speaker))
        (accuracy <- sum(diag(table(fit, temp$Speaker)))/sum(table(fit, 
            temp$Speaker)))
        cat(accuracy, "\n")
        return(list(Tab = Tab_ac, Accuracy = accuracy))
    }
  }

pingqingsheng/Robot0001 documentation built on May 5, 2019, 5:53 p.m.