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