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  • Book Overview & Buying Mastering Clojure Data Analysis
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Mastering Clojure Data Analysis

Mastering Clojure Data Analysis

By : Eric Richard Rochester
4.2 (5)
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Mastering Clojure Data Analysis

Mastering Clojure Data Analysis

4.2 (5)
By: Eric Richard Rochester
Buy this Book

Overview of this book

Table of Contents (17 chapters)
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Mastering Clojure Data Analysis
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Mastering Clojure Data Analysis
Credits
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Credits
About the Author
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About the Author
About the Reviewers
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About the Reviewers
www.PacktPub.com
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www.PacktPub.com
Preface
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Preface
Lock Free Chapter
1
Network Analysis – The Six Degrees of Kevin Bacon
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Network Analysis – The Six Degrees of Kevin Bacon
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Analyzing social networks
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Getting the data
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Understanding graphs
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Implementing the graphs
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Measuring social network graphs
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Visualizing the graph
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Summary
2
GIS Analysis – Mapping Climate Change
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GIS Analysis – Mapping Climate Change
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Understanding GIS
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Mapping the climate change
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Working with map projections
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Working with ArcGIS
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Summary
3
Topic Modeling – Changing Concerns in the State of the Union Addresses
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Topic Modeling – Changing Concerns in the State of the Union Addresses
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Understanding data in the State of Union addresses
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Understanding topic modeling
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Preparing for visualizations
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Setting up the project
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Getting the data
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Summary
4
Classifying UFO Sightings
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Classifying UFO Sightings
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Getting the data
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Extracting the data
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Dealing with messy data
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Visualizing UFO data
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Description
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Topic modeling descriptions
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Hoaxes
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Summary
5
Benford's Law – Detecting Natural Progressions of Numbers
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Benford's Law – Detecting Natural Progressions of Numbers
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Learning about Benford's Law
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Failing Benford's Law
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Case studies
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Summary
6
Sentiment Analysis – Categorizing Hotel Reviews
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Sentiment Analysis – Categorizing Hotel Reviews
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Understanding sentiment analysis
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Getting hotel review data
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Exploring the data
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Preparing the data
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Cross-validating the results
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Calculating error rates
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Using the Weka machine learning library
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Running the experiment
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Examining the results
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Improving the results
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Summary
7
Null Hypothesis Tests – Analyzing Crime Data
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Null Hypothesis Tests – Analyzing Crime Data
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Introducing confirmatory data analysis
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Understanding null hypothesis testing
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Understanding burglary rates
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Exploring the data
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Conducting the experiment
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Interpreting the results
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Summary
8
A/B Testing – Statistical Experiments for the Web
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A/B Testing – Statistical Experiments for the Web
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Defining A/B testing
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Conducting an A/B test
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Summary
9
Analyzing Social Data Participation
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Analyzing Social Data Participation
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Setting up the project
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Summary
10
Modeling Stock Data
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Modeling Stock Data
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Learning about financial data analysis
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Setting up the basics
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Getting prepared with data
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Analyzing the text
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Inspecting the stock prices
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Merging text and stock features
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Analyzing both text and stock features together with neural nets
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Predicting the future
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Taking it with a grain of salt
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Summary
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Index
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Index

Chapter 5. Benford's Law – Detecting Natural Progressions of Numbers

In this chapter, we'll look at Benford's Law; an interesting set of properties that are inherent in many naturally occurring sequences of numbers. For these sets of numbers, this observation predicts the distribution of initial digits.

The odd rule captures an interesting observation about the way numbers are distributed, and it's useful too. Benford's Law has been used as an evidence of fraud. If a sequence of numbers should be naturally occurring but Benford's Law indicates that they are not, then the sequence is likely to be fraudulent. For example, the daily balances in your bank account should follow Benford's Law, but if they don't, that may be evidence that someone is cooking the books.

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Tech Concepts
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Programming languages
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