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MACHINE LEARNING TECHNIQUES TO PREDICT GEOGRAPHIC TALENT FLOW

机译:预测地理人才流动的机器学习技术

摘要

Techniques are provided for predicting talent flow to and/or from a geographical region. In one technique, multiple entity profiles are stored and analyzed to generate training data that is labeled indicating whether a corresponding entity has moved to or moved from a region. A machine-learned prediction model is generated or trained based on the training data. Using the machine-learned prediction model, a prediction is made whether, for each entity corresponding to another entity profile, that entity will move to or move from a particular geographic region. Based on multiple predictions, a number of entities that are predicted to move to or move from the particular geographic region is determined. Talent flow data that is based on the number of entities is presented on a computer display.
机译:提供了用于预测进出地理区域的人才流动的技术。在一种技术中,存储和分析多个实体简档以生成训练数据,该训练数据被标记为指示相应的实体是否已移动到区域或从区域移动。基于训练数据生成或训练机器学习的预测模型。使用机器学习的预测模型,对于对应于另一个实体配置文件的每个实体,该实体是否将移动到特定地理区域或从特定地理区域移动做出预测。基于多个预测,确定被预测要移动到特定地理区域或从特定地理区域移动的多个实体。在计算机显示器上显示基于实体数量的人才流数据。

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