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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis FREE CHAPTER 2. Data Preprocessing 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Measuring distances


A metric on a set S of points is a function that satisfies these conditions for all x,y,z ∈ S:

  1. d(p,q) = 0 ⇔ p=q

  2. d(p,q) = d(p,q)

  3. d(p,q) ≤ d(p,r)+d(r,q)

Normally, we think of the number d(p,q) as the distance between p and q. With that interpretation, the three conditions are obvious: the distance from a point to itself is 0; if the distance between two points is 0, then they must be the same point; the distance from p to q is the same as the distance from q to p; the distance from p to q cannot be greater than the sum of the distances from p to r and from r to q. This last property is called the triangle inequality.

In mathematics, a non-empty set S together with a metric d defined on it is called a metric space. The simplest example is n-dimensional Euclidean space , where and d is the Euclidean metric,

In the case of two dimensions, , and . This is just the ordinary distance formula for points in the Cartesian plane, equivalent to the Pythagorean theorem, as Figure...

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