Pmml in Action (2nd Edition): Unleashing the Power of Open Standards for Data Mining and Predictive Analytics
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Numar articol:187911064
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Preț:234,00 Lei
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Anuntul a expirat la:22.12.2020, 14:33
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Specificatii
The data mining community has derived a broad foundation of
statistical algorithms and software solutions that has allowed
predictive analytics to become a standard approach used in science
and industry.For many years, much emphasis has been placed on the
development of predictive models. As a consequence, the market
place offers a range of powerful tools, many open-source, for
effective model building. However, once we turn to the operational
deployment and practical application of predictive solutions within
an existing IT infrastructure, we face a much more limited choice
of options. Often it takes months for models to be integrated and
deployed via custom code or proprietary processes.The Predictive
Model Markup Language (PMML) standard has reached a significant
stage of maturity and has obtained broad industry support, allowing
users to develop predictive solutions within one application and
use another to execute them. Previously, this was very difficult,
but with PMML, the exchange of predictive solutions between
compliant applications is now straightforward.The aim of this book
is to present PMML from a practical perspective. It contains a
variety of code snippets so that concepts are made clear through
the use of examples. Readers are assumed to have a basic knowledge
of predictive analytics and its techniques and so the book is
intended for data mining movers and shakers: anyone interested in
moving predictive analytic solutions between applications,
including students and scientists.PMML in Action is a great way to
learn how to represent your predictive solutions through a mature
and refined open standard. For the 2nd edition, the book has been
completely revised for PMML 4.1, the latest version of PMML. It
includes new chapters and an expanded description of how to
represent multiple models in PMML, including model ensemble,
segmentation, chaining, and composition. The book is divided into
six parts, taking you in a PMML journey in which language elements
and attributes are used to represent not only modeling techniques
but also data pre- and post-processing.With PMML, users benefit
from a single and concise standard to represent predictive models,
thus avoiding the need for custom code and proprietary
solutions.You too can join the PMML movement Unleash the power of
predictive analytics and data mining today
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