Elastic x-pack插件使用的机器学习算法 [英] Machine learning Algorithms used by Elastic x-pack plugin

问题描述

弹性X-pack插件可以预测我们数据的动态基线，并据此指定异常情况.

Elastic X-pack plugin predicts the dynamic baseline for our data and according to that specifies the anomalies out of the box.

所有这些东西都在幕后完成.我的问题是xpack如何从以前的数据中学习并动态更改基线.会使用特定的算法吗?

All these stuff are getting done behind the scene. My question is this how xpack learns from previous data and dynamically change the baseline. Does that use a specific algorithm?

有任何相关文件吗?

推荐答案

Elasticsearch机器学习中使用的算法是多种技术的组合，包括聚类，各种类型的时间序列分解，贝叶斯分布建模和相关性分析.

The algorithms used for Elasticsearch's Machine Learning are a mixture of techniques, including clustering, various types of time series decomposition, bayesian distribution modelling and correlation analysis.

以下是一些资源，您可以深入了解其工作原理:

Here are some resources where you can deep dive into how it works:

• 2018年度的Elastic {ON}演示了以下内容:弹性机器学习背后的数学"，可在此处获得录音: https://github .com/elastic/ml-cpp

• 2018's Elastic{ON} featured this presentation: "The Math Behind Elastic Machine Learning", a recording is available here: https://www.elastic.co/elasticon/conf/2018/sf/the-math-behind-elastic-machine-learning
• The C++ code which implements the core analytics for machine learning is available on github: https://github.com/elastic/ml-cpp

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