计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 306-312.doi: 10.11896/jsjkx.200500077
陈艳, 陈佳晴, 陈星
CHEN Yan, CHEN Jia-qing, CHEN Xing
摘要： 随着机器学习的兴起,算子数目飞速增长,组装算子需要搜索的解空间增大,流程组装时间指数倍增长,如何降低搜索解空间,从而降低组装时间,实现支持适应用户功能性需求的机器学习流程组装成为当前研究的热点。文中提出了一种基于层次标签、支持机器学习领域的流程组装方法。首先,从算子语义中提取标签,根据标签包含语义范围确定层次标签模型;其次,根据机器学习领域发现标签关系,确立领域组装模型,按照用户确定的功能性需求,确定最终领域标签模型;最后领域内算子与标签语义绑定,确定领域内算子关系模型,根据组装规则组装算子,形成满足用户功能性需求的全部算子流程。最后给出了支持该方法的实例,用以说明该方法的可行性;提出结果验证标准,用以说明结果的正确性与完整性。
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