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Clojure for Data Science

You're reading from   Clojure for Data Science Statistics, big data, and machine learning for Clojure programmers

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781784397180
Length 608 pages
Edition 1st Edition
Languages
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Author (1):
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Henry Garner Henry Garner
Author Profile Icon Henry Garner
Henry Garner
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Toc

Table of Contents (12) Chapters Close

Preface 1. Statistics FREE CHAPTER 2. Inference 3. Correlation 4. Classification 5. Big Data 6. Clustering 7. Recommender Systems 8. Network Analysis 9. Time Series 10. Visualization Index

Matrices


A matrix is a two-dimensional grid of numbers. The dimensions are expressed as the number of rows and columns in the matrix.

For example, A is a matrix with four rows and two columns:

In mathematical notation, a matrix will usually be assigned to a variable with an upper-case letter to distinguish it from other variables in an equation.

We can construct a matrix from our dataset using Incanter's incanter.core/to-matrix function:

(defn ex-3-16 []
  (->> (swimmer-data)
       (i/$ ["Height, cm" "Weight"])
       (i/to-matrix)))

Incanter also defines the incanter.core/matrix function that will take a sequence of scalar values or a sequence of sequences and convert them into a matrix if it can:

(defn ex-3-17 []
  (->> (swimmer-data)
       (i/$ "Height, cm")
       (i/matrix)))

If you run this in the REPL, the output will be a summary of the contents of the matrix:

  A 859x1 matrix
 ---------------
 1.66e+02
 1.92e+02
 1.73e+02
 ...
 1.88e+02
 1.87e+02
 1.83e+02

Incanter returns...

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