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Mining High Utility Itemsets Using Bio-Inspired Algorithms: A Diverse Optimal Value Framework

IEEE Access, 2018
Mining high utility itemsets (HUI) is an interesting research problem in the field of data mining and knowledge discovery. Recently, bio-inspired computing has attracted considerable attention, leading to the development of new algorithms for mining HUIs.
Wei Song, Chaomin Huang
doaj +1 more source

Cost-Sensitive Decision Tree with Multiple Resource Constraints [PDF]

Resource constraints are commonly found in classification tasks. For example, there could be a budget limit on implementation and a deadline for finishing the classification task.
Chia-Chi WU, Kwei TANG, Yen-Liang CHEN
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On the Complexity of Rule Discovery from Distributed Data [PDF]

This paper analyses the complexity of rule selection for supervised learning in distributed scenarios. The selection of rules is usually guided by a utility measure such as predictive accuracy or weighted relative accuracy. Other examples are support and
Scholz, Martin
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Utility-Based Data Mining Workshop Chairs: [PDF]

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Bianca Zadrozny, Gary Weiss, Maytal Saar-tsechansky +2 more
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TKU-PSO: An Efficient Particle Swarm Optimization Model for Top-K High-Utility Itemset Mining.

International Journal of Interactive Multimedia and Artificial Intelligence
Top-k high-utility itemset mining (top- HUIM) is a data mining procedure used to identify the most valuable patterns within transactional data. Although many algorithms are proposed for this purpose, they require substantial execution times when the ...
Simen Carstensen, Jerry Chun Wei Lin
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Mining actionable combined high utility incremental and associated sequential patterns. [PDF]