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Active learning for interactive labeling of new device types based on limited feedback

机译:基于有限反馈的新设备类型的交互式标签主动学习

摘要

In one embodiment, a device clusters traffic feature vectors for a plurality of endpoints in a network into a set of clusters. Each traffic feature vector comprises traffic telemetry data captured for one of the endpoints. The device selects one of the clusters for labeling, based in part on contextual data associated with the clusters that was not used to form the clusters. The device obtains a device type label for the selected cluster by providing data regarding the selected cluster and the contextual data associated with that cluster to a user interface. The device provides the device type label and the traffic feature vectors associated with the selected cluster for training a machine learning-based device type classifier.
机译:在一个实施例中,设备群集用于网络中的多个端点的业务特征向量进入一组集群。 每个流量特征向量包括捕获的流量遥测数据,该数据捕获了一个端点。 该设备选择用于标记的一个群集,部分地基于与不用于形成群集的群集相关联的上下文数据。 该设备通过提供关于所选群集的数据和与该群集相关联的群集到用户界面的数据来获得所选集群的设备类型标签。 该设备提供设备类型标签和与所选集群关联的流量特征向量,用于培训基于机器学习的设备类型分类器。

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