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plajner-0490309.pdf

🔗 Source: library.utia.cas.cz

📊 Size: 482 KB

👤 Author: Václav Kratochvíl, Jirina Vejnarová (editors)

⬇️ Downloads: 25

Summary

The authors propose a generalization of a previously used algorithm for parameter learning of Bayesian Networks under monotonicity conditions, allowing both parents and children in the network to have multiple states. The algorithm is tested on two different data sets, and the results show that the proposed method outperforms the EM algorithm for small data sets and provides comparable results for larger sets. The method is applied to the domain of Computerized Adaptive Testing (CAT), where monotonicity conditions are used to guarantee that students having certain skills will have a higher probability of answering questions correctly.

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Description

The authors propose a generalization of a previously used algorithm for parameter learning of Bayesian Networks under monotonicity conditions, allowing both...

Technical Information

File Format: PDF
File Size: 482 KB
Pages: 12
Language: EN
Author: Václav Kratochvíl, Jirina Vejnarová (editors)
Total Downloads: 25
Last Updated: 2 months ago

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