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This article compiles recent model articles for students, summarizing key resources on probability models, including Monte Carlo simulation, Markov processes, queueing theory, and Bayesian methods, with links to detailed explanations and applications.
The paper introduces a constraint‑adaptive rule‑set learning framework (CRSL) that combines a constraint‑aware decision‑tree miner (CARM), a rule‑sorting filter, and a Bayesian rule‑combination selector (CBRS), achieving superior performance and interpretability on benchmark and massive industrial fraud‑detection data and being deployed in Alipay’s risk‑analysis platform.
This article compiles recent resources on probability and statistical modeling, covering Monte Carlo simulation, Markov processes, queueing theory, and Bayesian methods, providing direct links to each detailed write‑up for students and researchers seeking comprehensive study material.