Application using text2vec examples

In this section, we will analyze the performance of logistic regression on various examples of text2vec.

How to do it...

Here is how we apply text2vec:

1. Load the required packages and dataset:

library(text2vec) 
library(glmnet) 
data("movie_review") 

2. Function to perform Lasso logistic regression, and return the train and test AUC values:

logistic_model <- function(Xtrain,Ytrain,Xtest,Ytest)
{ 
  classifier <- cv.glmnet(x=Xtrain, y=Ytrain, 
  family="binomial", alpha=1, type.measure = "auc", 
  nfolds = 5, maxit = 1000) 
  plot(classifier) 
  vocab_test_pred <- predict(classifier, Xtest, type = "response") 
  return(cat("Train AUC ...