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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
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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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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

Use case and data


We have four artificial sensors installed in the field and our digital control system collects the information from these sensors. We need to put a real-time analysis system in place. We need a  feature in that system to cluster the incoming data and display those clusters in real time in a digital dashboard. The idea is users watching those dashboards will be alerted immediately for some anomaly or malfunction if they see unusual cluster patterns.

This example is inspired by the sensor network example given in pubnub at: https://www.pubnub.com/developers/realtime-data-streams/sensor-network/.

The following diagram should sufficiently visualize our use case:

What we have here is a lambda architecture (http://lambda-architecture.net/).

Our digital control system is generating data at a particular rate. It has the following sensors installed:

  • Radiation sensor (millrads/hour)--the range of data is between 195 and 202
  • Humidity (%)--the range of data is between 74 and 82
  • Temperature...
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