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

机译:使用机器学习进行分类和预测信息技术事件原因的系统和方法

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:本公开提供了基于确定事件的可能性与问题相关的可能性,基于确定分支的决策树来分类事件的差异,基于确定事件的决策树来对事件进行分类,该系统和方法基于确定分支的决策树。 ,并预测新事件是否与问题有关。 可以从一组事件(例如,在一定时间段内报告的情况)中提取特征,包括与问题和与问题无关的问题有关的事件。 与问题有关的事件和与问题无关的事件的一部分可用于培训逻辑回归模型或生成决策树。 训练有素的逻辑回归模型可用于确定几率比率或预测新事件是否与问题有关。

著录项

  • 公开/公告号US2021382775A1

    专利类型

  • 公开/公告日2021-12-09

    原文格式PDF

  • 申请/专利权人 SERVICENOW INC.;

    申请/专利号US202117445806

  • 申请日2021-08-24

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

  • 国家 US

  • 入库时间 2024-06-14 22:30:20

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