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SYSTEMS AND METHODS FOR CLASSIFYING AND PREDICTING THE CAUSE OF INFORMATION TECHNOLOGY INCIDENTS USING MACHINE LEARNING

机译:使用机器学习对信息技术事件的原因进行分类和预测的系统和方法

摘要

The present disclosure provides systems and methods for classifying incidents based on determining an odds ratio that represents a likelihood of an incident being related to the problem, classifying incidents based on determining a decision tree that forms branches based on whether a feature is present in the incident, and predicting whether a new incident is related to a problem. Features may be extracted from a set of incidents (e.g., that are reported over a certain time period) that include incidents related to a problem and incidents not related to the problem. The incidents related to the problem and a portion of the incidents not related to the problem may be used to train a logistic regression model or generate a decision tree. The trained logistic regression model may be used to determine the odds ratios or predict whether a new incident is related to a problem.
机译:本公开提供了用于基于确定代表事件与事件有关的可能性的比值比对事件进行分类的系统和方法,基于基于事件中是否存在特征来确定形成分支的决策树来对事件进行分类。 ,并预测新事件是否与问题有关。可以从一组事件中提取特征(例如,在特定时间段内报告的事件),这些事件包括与问题有关的事件和与该问题无关的事件。与问题有关的事件以及与问题不相关的事件的一部分可以用于训练逻辑回归模型或生成决策树。训练后的逻辑回归模型可用于确定比值比或预测新事件是否与问题有关。

著录项

  • 公开/公告号US2020250022A1

    专利类型

  • 公开/公告日2020-08-06

    原文格式PDF

  • 申请/专利权人 SERVICENOW INC.;

    申请/专利号US201916267114

  • 申请日2019-02-04

  • 分类号G06F11/07;G06F11/34;G06K9/62;G06F17/18;

  • 国家 US

  • 入库时间 2022-08-21 11:20:19

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