| filterTweetsMachineLearning {needmining} | R Documentation |
Classify needs based on machine learning
Description
filterTweetsMachineLearning classifies a list of Tweets as
needs based on the random forest machine learning algorithm
Usage
filterTweetsMachineLearning(dataToClassify, trainingData)
Arguments
dataToClassify |
a dataframe containing the Tweet messages to classify |
trainingData |
a dataframe containing Tweets messages with a given classification (0=not a need, 1=a need) |
Details
This function uses a machine learning algorithm (random forest) to classify needs based on their content. It needs a training data set with classified needs (indicated by 0=not a need, 1=a need). This function used code fragments from the archived R packages maxent and RTextTools. The authors are Timothy P. Jurka, Yoshimasa Tsuruoka, Loren Collingwood, Amber E. Boydstun, Emiliano Grossman, Wouter van Atteveldt
Value
a dataframe with classified data
Author(s)
Dorian Proksch <dorian.proksch@hhl.de>
Examples
data(NMTrainingData)
data(NMdataToClassify)
smallNMTrainingData <- rbind(NMTrainingData[1:75,], NMTrainingData[101:175,])
smallNMdataToClassify <- rbind(NMdataToClassify[1:10,], NMdataToClassify[101:110,])
results <- filterTweetsMachineLearning(smallNMdataToClassify, smallNMTrainingData)