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Clojure Data Analysis Cookbook - Second Edition

You're reading from   Clojure Data Analysis Cookbook - Second Edition Dive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784390297
Length 372 pages
Edition 2nd Edition
Languages
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Author (1):
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Eric Richard Rochester Eric Richard Rochester
Author Profile Icon Eric Richard Rochester
Eric Richard Rochester
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Toc

Table of Contents (14) Chapters Close

Preface 1. Importing Data for Analysis 2. Cleaning and Validating Data FREE CHAPTER 3. Managing Complexity with Concurrent Programming 4. Improving Performance with Parallel Programming 5. Distributed Data Processing with Cascalog 6. Working with Incanter Datasets 7. Statistical Data Analysis with Incanter 8. Working with Mathematica and R 9. Clustering, Classifying, and Working with Weka 10. Working with Unstructured and Textual Data 11. Graphing in Incanter 12. Creating Charts for the Web Index

Loading CSV and ARFF files into Weka

Weka is most comfortable when using its own file format: the Attribute-Relation File Format (ARFF). This format includes the types of data in the columns and other information that allow it to be loaded incrementally, and both of these can be important features. Because of this, Weka can load data more reliably. However, Weka can still import CSV files, and when it does, it attempts to guess the type of data in the columns.

In this recipe, we'll see what's necessary to load data from a CSV file and an ARFF file.

Getting ready

First, we'll need to add Weka to the dependencies in our Leiningen project.clj file:

(defproject d-mining "0.1.0-SNAPSHOT"
  :dependencies [[org.clojure/clojure "1.6.0"]
                 [nz.ac.waikato.cms.weka/weka-dev "3.7.11"]])

Then we'll import the right classes into our script or REPL:

(import [weka.core.converters ArffLoader CSVLoader]
        [java.io File])

Finally, we'll...

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