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doInstall <- TRUE | |
toInstall <- c("twitteR", "dismo", "maps", "ggplot2") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
searchTerm <- "#rstats" | |
searchResults <- searchTwitter(searchTerm, n = 1000) # Gather Tweets | |
tweetFrame <- twListToDF(searchResults) # Convert to a nice dF | |
userInfo <- lookupUsers(tweetFrame$screenName) # Batch lookup of user info |
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rm(list = ls()) | |
doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
toInstall <- c("zoo", "tm", "ggplot2", "Snowball") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# From: http://www.cnn.com/2012/10/03/politics/debate-transcript/index.html | |
Transcript <- readLines("https://raw.github.com/dsparks/Test_image/master/Denver_Debate_Transcript.txt") | |
head(Transcript, 20) |
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# FILE: Classifying Breast Cancer as Benign or Malignant | |
# AUTHOR: Timothy P. Jurka | |
library(RTextTools); | |
# GET THE BREAST CANCER DATA FROM http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.names | |
data <- read.csv("http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/breast-cancer-wisconsin.data",header=FALSE) | |
data <- data[-1] | |
# ADD TEXTUAL DESCRIPTORS FOR EACH MASS CHARACTERISTIC FOR THE DOCUMENT-TERM MATRIX |