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R Data Analysis Projects

You're reading from   R Data Analysis Projects Build end to end analytics systems to get deeper insights from your data

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788621878
Length 366 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Gopi Subramanian Gopi Subramanian
Author Profile Icon Gopi Subramanian
Gopi Subramanian
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Toc

Table of Contents (9) Chapters Close

Preface 1. Association Rule Mining 2. Fuzzy Logic Induced Content-Based Recommendation FREE CHAPTER 3. Collaborative Filtering 4. Taming Time Series Data Using Deep Neural Networks 5. Twitter Text Sentiment Classification Using Kernel Density Estimates 6. Record Linkage - Stochastic and Machine Learning Approaches 7. Streaming Data Clustering Analysis in R 8. Analyze and Understand Networks Using R

Building an RShiny application


Our RShiny application will have the following features,

  • Load the RLdata500 from the RecordLinkage package and display to the user
  • Implement the weights algorithm and display the weight range as a histogram
  • Allow the user to select the lower and upper thresholds of weights for classification
  • Based on the user-selected threshold, do a record matching and display the duplicate entities discovered.

Let us see the code for the user interface:

ui <- fluidPage(
  navbarPage("Record Linkage",
    tabPanel("Load"
     , dataTableOutput("records")
    ),
    tabPanel("Weights Method"
     ,plotOutput("weightplot")
     ,sliderInput("lowerthreshold", "Weight Lower threshold:",
        min = 0.0, max = 1.0,
        value =0.2)
     ,sliderInput("upperthreshold", "Weight Upper threshold:",
        min = 0.0, max = 1.0,
        value =0.5)

     ,dataTableOutput("weights")
     )
  )
)

There are two panels, one to show the RLdata500 and an other one to show the results of the...

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