Towards a Theory for Designing Machine Learning Systems for Complex Decision Making Problems

Name: Towards a Theory for Designing Machine Learning Systems for Complex Decision Making Problems
Brand: Cuvillier
SKU: 9783736972001
Price: 268.34 RON
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Autor: Schahin Tofangchi

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Editura: Cuvillier

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The ubiquitousness of data and the emergence of data-driven machine learning approaches provide new...

Informații despre carte

Autor

Schahin Tofangchi

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2020

Pagini

202

EAN

9783736972001

ISBN

3736972008

Enbook ID

32741991

Editura

Cuvillier

Greutate

245

Dimensiuni

148 x 210 x 12

Descriere completă

The ubiquitousness of data and the emergence of data-driven machine learning approaches provide new means of creating insights. However, coping with the great volume, velocity, and variety of data requires improved data analysis methods. This dissertation contributes a nascent design theory, named the Division-of-Labor framework, for developing complex machine learning systems that can not only address the challenges of big data but also leverage their characteristics to perform more sophisticated analyses. I evaluate the proposed design principles in three practical settings, in which I apply the principles to design machine learning systems that (i) support treatment decision making for cancer patients, (ii) provide consumers with recommendations on two-sided platforms, and (iii) address a trade-off between efficiency and comfort in the context of autonomous vehicles. The evaluations partially validate the proposed theory, but also show that some principles require further attention in order to be practicable.

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Towards a Theory for Designing Machine Learning Systems for Complex Decision Making Problems

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