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Systems and methods for predicting lost demand using machine learning architectures

机译:使用机器学习架构预测损失需求的系统和方法

摘要

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of: providing, via an electronic platform, access to one or more order placement user interfaces; collecting order placement information associated with the one or more order placement user interfaces; analyzing, by a conversion determination network of a machine learning architecture, the order placement information; generating actual conversion information for client sessions based on the actual availability of the order placement options during the client sessions; generating predicted conversion information for the client sessions based on a full availability of all of the order placement options during the client sessions; and generating lost demand information based, at least in part, on the actual conversion information and the predicted conversion information. Other embodiments are disclosed herein.
机译:包括一个或多个处理器的系统和方法和存储被配置为在一个或多个处理器上运行的计算指令的一个或多个非暂时性存储设备,并通过电子平台访问:通过电子平台访问一个或多个订单放置用户界面;收集与一个或多个订单放置用户界面相关的订单放置信息;通过机器学习架构的转换确定网络分析,订单放置信息;基于客户端会话期间订单放置选项的实际可用性为客户端会话生成实际转换信息;基于客户端会话期间的所有订单放置选项的完全可用性生成用于客户端会话的预测转换信息;并且至少部分地基于实际转换信息和预测的转换信息生成丢失的需求信息。本文公开了其他实施例。

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