首页> 外国专利> PREFETCHING AND/OR COMPUTING RESOURCE ALLOCATION BASED ON PREDICTING CLASSIFICATION LABELS WITH TEMPORAL DATA

PREFETCHING AND/OR COMPUTING RESOURCE ALLOCATION BASED ON PREDICTING CLASSIFICATION LABELS WITH TEMPORAL DATA

机译:基于预测与时间数据的分类标签的预取和/或计算资源分配

摘要

Methods, systems and computer program products are provided for prefetching information and/or (pre)allocating computing resources based on predicting classification labels with temporal data. A trained temporal classification model forecasts events (e.g., too numerous for individual modeling) by predicting classification labels indicating whether events will occur, or a number of occurrences of the events, during each of a plurality of future time intervals. Time-series datasets, indicating whether events occurred, or a number of occurrences of the events, during each of a plurality of past time intervals, are transformed into temporal classification datasets. Classifications may be based, at least in part, on extracted features, such as data seasonality, temporal representation, statistical and/or real-time features. Classification labels are used to determine whether to take one or more actions, such as, for example, prefetching information or (pre)allocating a computing resource.
机译:提供基于预测具有时间数据的分类标签的预取信息和/或(前)分配计算资源的方法,系统和计算机程序产品。 训练有素的时间分类模型通过预测指示事件是否会发生的分类标签,或者在多个未来时间间隔中的每一个期间进行事件的分类标签,或者发生事件的次数。 时间序列数据集,指示是否发生事件,或者在多个过去的时间间隔中的每一个中发生一些事件发生,或者发生在时间间隔中的每一个中。 分类可以至少部分地基于提取的特征,例如数据季节性,时间表示,统计和/或实时特征。 分类标签用于确定是否采取一个或多个动作,例如预取信息或(前)分配计算资源。

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