Name: Boosted Statistical Relational Learners
Price: 51.9 CHF
Availability: InStock
ISBN: 978-3-319-13643-1

productDetailPageQuery

Springer

This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several statistical relational learning (SRL) methods. These methods combine the expressiveness of first-order logic with the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real-world applications. The models are highly attractive due to their compactness and comprehensibility, but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been successfully applied in several SRL settings and have been adapted to various real problems, from information extraction in text to medical issues.

Actual product image Boosted Statistical Relational Learners (English, Paperback, Jude Shavlik, Kristian Kersting, Sriraam Natarajan, Tushar Khot)

Key specifications

Topic

Subtopic

Language

Number of pages

Book cover

Boosted Statistical Relational Learners

Reference books

30-day right of return – unopened

General information

Book properties

Voluntary climate contribution

Product dimensions

Search

Settings

Customer account

Comparison lists

Watch lists

Cart

Boosted Statistical Relational Learners

In Detail

Compare products

Goes with

Boosted Statistical Relational Learners

In Detail

Description

Specifications

Price trend

Warranty and return rates

Questions about this product0

Product ratings0

Compare products

Similar products

Sales rank in Reference books

Goes with

Often bought together