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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Test Data Engineering - Latent Rank Analysis, Biclustering, and Bayesian Network (Hardcover, 1st ed. 2022)
Loot Price: R4,014
Discovery Miles 40 140
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Test Data Engineering - Latent Rank Analysis, Biclustering, and Bayesian Network (Hardcover, 1st ed. 2022)
Series: Behaviormetrics: Quantitative Approaches to Human Behavior, 13
Expected to ship within 12 - 17 working days
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This is the first technical book that considers tests as public
tools and examines how to engineer and process test data, extract
the structure within the data to be visualized, and thereby make
test results useful for students, teachers, and the society. The
author does not differentiate test data analysis from data
engineering and information visualization. This monograph
introduces the following methods of engineering or processing test
data, including the latest machine learning techniques: classical
test theory (CTT), item response theory (IRT), latent class
analysis (LCA), latent rank analysis (LRA), biclustering
(co-clustering), and Bayesian network model (BNM). CTT and IRT are
methods for analyzing test data and evaluating students' abilities
on a continuous scale. LCA and LRA assess examinees by classifying
them into nominal and ordinal clusters, respectively, where the
adequate number of clusters is estimated from the data.
Biclustering classifies examinees into groups (latent clusters)
while classifying items into fields (factors). Particularly, the
infinite relational model discussed in this book is a biclustering
method feasible under the condition that neither the number of
groups nor the number of fields is known beforehand. Additionally,
the local dependence LRA, local dependence biclustering, and
bicluster network model are methods that search and visualize
inter-item (or inter-field) network structure using the mechanism
of BNM. As this book offers a new perspective on test data analysis
methods, it is certain to widen readers' perspective on test data
analysis.
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