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MACHINE LEARNING SYSTEMS AND METHODS FOR PREDICTIVE ENGAGEMENT

机译:用于预测接触的机器学习系统和方法

摘要

A machine learning (ML) process can include teaching, with a teaching set, a first ML algorithm to generate one or more machine -predicted results. One or more weights can be generated based on the one or more machine-predicted results and the teaching set. A second ML algorithm can be generated based on the one or more weights. Via the second ML algorithm, one or more machine-learned results can be generated. A description of one or more candidates can be received. Based on the one or more machine-learned results, a respective likelihood of interest in a CCG class of positions for each of the one or more candidates can be generated. A respective communication can be transmitted to each of a subset of the one or more candidates open to the respective likelihood of interest in the CCG class of positions for the subset above a threshold.
机译:机器学习(ML)过程可以包括教学,具有教学集,第一ML算法生成一个或多个机器预测结果。可以基于一个或多个机器预测结果和教学集生成一个或多个权重。可以基于一个或多个权重生成第二ML算法。通过第二ML算法,可以生成一个或多个计算机学习的结果。可以接收一个或多个候选者的描述。基于一个或多个机器学习的结果,可以生成一个或多个机器学习的结果,可以生成一个或多个候选者中的每一个的CCG位置的感兴趣的似然。可以将相应的通信发送到一个或多个候选的每个子集中的每一个,其对阈值上方的子集的CCG位置中的CCG类位置中的相应可能性。

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