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R Deep Learning Projects

You're reading from   R Deep Learning Projects Master the techniques to design and develop neural network models in R

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788478403
Length 258 pages
Edition 1st Edition
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Authors (2):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Pablo Maldonado Pablo Maldonado
Author Profile Icon Pablo Maldonado
Pablo Maldonado
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Toc

Sentiment analysis from movie reviews

Let's continue with the IMDb data and put into practice the ideas from the previous sections. In this section, we will use a few familiar packages, like tidytext, plyr and dplyr, as well as the excellent text2vec by Dimitriy Selivanov, which was released in 2017, and the well-known caret package by Max Kuhn.

Data preprocessing

We need to prepare our data for the algorithm.

First, a few imports that will be necessary:

library(plyr)
library(dplyr)
library(text2vec)
library(tidytext)
library(caret)

We will use the IMDb data as before:

imdb <- read.csv("./data/labeledTrainData.tsv", encoding = "utf-8", quote = "", sep="\t", stringsAsFactors = F)
...
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