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Mastering Clojure Data Analysis

You're reading from  Mastering Clojure Data Analysis

Product type Book
Published in May 2014
Publisher
ISBN-13 9781783284139
Pages 340 pages
Edition 1st Edition
Languages
Author (1):
Eric Richard Rochester Eric Richard Rochester
Profile icon Eric Richard Rochester

Table of Contents (17) Chapters

Mastering Clojure Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Network Analysis – The Six Degrees of Kevin Bacon 2. GIS Analysis – Mapping Climate Change 3. Topic Modeling – Changing Concerns in the State of the Union Addresses 4. Classifying UFO Sightings 5. Benford's Law – Detecting Natural Progressions of Numbers 6. Sentiment Analysis – Categorizing Hotel Reviews 7. Null Hypothesis Tests – Analyzing Crime Data 8. A/B Testing – Statistical Experiments for the Web 9. Analyzing Social Data Participation 10. Modeling Stock Data Index

Topic modeling descriptions


Another way to gain a better understanding of the descriptions is to use topic modeling. We learned about this text mining and machine learning algorithm in Chapter 3, Topic Modeling – Changing Concerns in the State of the Union Addresses. In this case, we'll see if we can use it to create topics over these descriptions and to pull out the differences, trends, and patterns from this set of texts.

First, we'll create a new namespace to handle our topic modeling. We'll use the src/ufo_data/tm.clj file. The following is the namespace declaration for it:

(ns ufo-data.tm
  (:require [clojure.java.io :as io]
            [clojure.string :as str]
            [clojure.pprint :as pp])
  (:import [cc.mallet.util.*]
           [cc.mallet.types InstanceList]
           [cc.mallet.pipe
            Input2CharSequence TokenSequenceLowercase
            CharSequence2TokenSequence SerialPipes
            TokenSequenceRemoveStopwords
            TokenSequence2FeatureSequence]
   ...
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