搏斗 发表于 2025-3-30 08:51:08

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creditor 发表于 2025-3-30 15:13:04

Incremental Response Modeling Based on Segmentation Approach Using Uplift Decision Trees,g chapter evaluates the nexus between budgetary policy and confidence, summarises the key failings of fiscal activism, and suggests fiscal policy goals. .The book will appeal to university lecturers and researchers in macroeconomics and economists working in government and the private sector..978-3-319-90158-9

Muscularis 发表于 2025-3-30 19:08:47

Development of Issue Sets from Social Big Data: A Case Study of Green Energy and Low-Carbon,s redundant for the universality of man, his scientific pursuit and historical experience. The conundrum of universality and power calls for a systematic critique of .instrumental reason., its practical applica978-3-031-69547-6978-3-031-69545-2

北极人 发表于 2025-3-30 23:56:31

A Fuzzy Rule-Based Learning Algorithm for Customer Churn Prediction,h theoretical and computational material to allow the advanced undergraduate or beginning graduate student to overcome this deficiency and be able to work independently or in advanced courses. The book is inten978-94-007-2635-2978-94-007-2636-9

肉身 发表于 2025-3-31 03:33:22

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花束 发表于 2025-3-31 05:59:49

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刺激 发表于 2025-3-31 11:46:43

https://doi.org/10.1007/BFb0081344lds. Extensive experiments carried on both real-life and synthetic databases show that the proposed approaches can efficiently discover the complete set of HAUIs when considering multiple minimum average-utility thresholds.

acquisition 发表于 2025-3-31 14:24:34

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充气女 发表于 2025-3-31 20:29:14

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Innocence 发表于 2025-3-31 22:02:53

Adding directed colimits to a subcategory,s attributes. The resultant clusters are found to be representative of different types of truck stops. The characterized truck stoppages can be useful for dynamic trip planning, behavior modeling of drivers and traffic incident detection.
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查看完整版本: Titlebook: Advances in Data Mining. Applications and Theoretical Aspects; 16th Industrial Conf Petra Perner Conference proceedings 2016 Springer Inter