*Take $10 off when you spend $50+! Use code NEWYEAR10. Ends Mon 5 Jan. T&Cs apply.
Track My Order
Help Centre
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore
Get Free Shipping on orders over $79
Astronomy and Big Data : A Data Clustering Approach to Identifying Uncertain Galaxy Morphology - Kieran Jay Edwards

Astronomy and Big Data

A Data Clustering Approach to Identifying Uncertain Galaxy Morphology

By: Kieran Jay Edwards, Mohamed Medhat Gaber

eText | 12 April 2014

At a Glance

eText

$159.01

or 4 interest-free payments of $39.75 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.
With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as "Uncertain". This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Selection (IFS). The book shows the use of state-of-the-art classification techniques, Random Forests and Support Vector Machines to validate the acquired results. It is concluded that a vast majority of these galaxies are, in fact, of spiral morphology with a small subset potentially consisting of stars, elliptical galaxies or galaxies of other morphological variants.
on
Desktop
Tablet
Mobile

You Can Find This eBook In

Non-FictionComputing & I.T.Computer ScienceArtificial IntelligenceScienceAstronomy, Space & TimeDatabasesData MiningEngineering & TechnologyTechnology in GeneralEngineering in GeneralMathematics
Probability & Statistics

Other Editions and Formats

Paperback

Published: 3rd September 2016

View Product

More in Artificial Intelligence

HBR Guide to Generative AI for Managers : HBR Guide - Elisa Farri

eBOOK

HBR Guide to Generative AI for Managers

HBR Guide

eBook

RRP $37.15

$29.99

19%
OFF
AI-Powered Search - Trey Grainger

eBOOK

AI-Powered Search

eBook

$52.99

AI : The End of Human Race - Alex Wood

eBOOK

AI

The End of Human Race

eBook

$16.99

This product is categorised by