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 MessagePosté le: Jeu 6 Juil - 10:18 (2017)    Sujet du message: Transparent Data Mining For Big And Small Data Studies In Répondre en citant Back to top


Transparent Data Mining for Big and Small Data (Studies in Big Data)
by Tania Cerquitelli
rating: ( reviews)


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This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.

As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.



Details:
rank:
price: $89.12
bound:
publisher: Springer; 1st ed. 2017 edition (May 10, 2017)
lang: English
asin:
isbn: 3319540238, 978-3319540238,
weight: 1.1 pounds (
filesize:




Transparent Data Mining for Big and Small Data (Studies in Big Data) download from SaberCatHost pdf

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Despite being generated from private data, algorithm-generated models are not personal data in the strict meaning of lawThis book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutionsWith contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.Studies in Big Data Free Preview 2017 Transparent Data Mining for Big and Small Data Editors: Cerquitelli, Tania, Quercia, Daniele, Pasquale, Frank (Eds.) Describes the negative effects of opaque "black-box" algorithms in technical detail Offers solutions for the implementation of transparent algorithms Discusses specific state-of-the-art transparent algorithms as well as new applications made possible by transparent algorithms see more benefits More information Accept Over 10 million scientific documents at your fingertips Browse by Discipline Biomedicine Business and Management Chemistry Computer Science Earth Sciences Economics Education Engineering Environment Geography History Law Life Sciences Literature Materials Science Mathematics Medicine & Public Health Pharmacy Philosophy Physics Political Science and International Relations Psychology Social Sciences Statistics Our Content Journals Books Book Series Protocols Reference Works Other Sites Springer.com SpringerProtocols SpringerMaterials AdisInsight Help & Contacts Contact Us Impressum Legal Springer International Publishing AGBUY & SELL $135.00 Add the $0.00 item to the cart and check out.After shipping is added in, the total will be $0.00If you are buying more than one item today, use the add to bookbag link at the top of the screenSupportthe footnotesNowadays, algorithms are used to produce, distribute, and filter news articlesImportant datesHutton and Henderson (tnhh)introduce new approaches for obtaining sustained and meaningful consent (Chapter Beyond the EULA: Improving Consent for Data Mining)1If you have any question or information request on this workshobook, please send an email to tania.cerquitelli AT polito DOT it.

Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented(ieMaak jouw account aan, draag iedere dag bij aan jouw community, ontdek nieuwe video'sThe first concerns data releaseConsider buyback value Buy Low! Sell High!Want to know the real cost of your book? You have to understand how much it'll be worth when you sell it at the end of the termStill, the accuracy achieved by deep neural networks has been so far unbeatenThe Uber-BOT's Multi-Item Price Optimization calculates the lowest total price for all your items at once, maximizing promotions, and minimizing shipping3-5 for standard) (standard) btwn Mon 07/10 & Thu (fast) this Monday the 10th (ASAP) Saturday filter OUT these keywords (Comma Separated) Sometimes you just need the ability to remove any item with a particular word in the commentsThey could perpetuate racial discrimination by refusing mortgages based on factors imperfectly tied to racePlease put your arms back togetherTrue story, last time I made that same Waynes World reference, five minutes later I ran into Mike Myers standing on the sidewalk with his kid in NYCHere there are three stepsWith contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical useAlgorithms could recommend activities that minimize health risks only for a subset of the population because of biased training dataWe're working on a new format for books, and would like your opinionAlgorithms are increasingly impacting our livestypes of items: physical items (Books,Cds.) New items Used Items Rental Items Why buy when you can rent!?!?Instead of buying the book today and selling it at the end of the semester, rent it for significantly less than the used price 07f867cfac



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