Unverified50% confidenceFactExact time
Model drift is a core problem that AI trading systems must continuously address, referring to the phenomenon in which a model's performance degrades over time in a production environment, and it is usually divided into two categories: data drift and concept drift.
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10/16/2026
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Verified模型漂移通常分为数据漂移和概念漂移两类,数据漂移指输入数据统计分布随时间变化,概念漂移指输入与输出关系本身发生变化79% similarVerifiedModel drift refers to the decline in model prediction quality caused by changes in the distribution of input data in the production environment over time.76% similarUnverifiedConcept drift refers to the statistical relationship between input data and the target variable changing over time, causing a previously trained model to gradually become ineffective; it is usually divided into three types: abrupt, gradual, and periodic.72% similarUnverified概念漂移(Concept Drift)指输入变量与目标变量之间的映射关系本身发生变化70% similarUnverified模型路由脱胎于分布式系统中的负载均衡与请求调度思想69% similar
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