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什么是最合适的机器学习 model 来检测时间序列数据中的突变点？

[英]What is the most appropriate machine learning model to detect abrupt changepoints in time-series data?

原文 2020-05-25 13:21:12 8 1 machine-learning/ data-science/ anomaly-detection

I have a dataframe with a column for time in which anomalies occur.我有一个 dataframe 列，其中有一个异常发生时间的列。 The anomalies are of a sudden changepoint in the time column.异常是时间列中的突然变化点。

The changepoint is the blue point in the graph.变化点是图中的蓝点。

My goal is to identify these points as anomalies and mark them.我的目标是将这些点识别为异常并标记它们。

I've tried searching for anomaly detection ML models for this problem such as:我已经尝试为这个问题搜索异常检测 ML 模型，例如：

Low pass filter低通滤波器
SVM支持向量机
AR增强现实
ARIMA有马
BOCD BOCD

None of these ML models succeed at identifying these anomalous points but maybe i missed something.这些 ML 模型都没有成功识别这些异常点，但也许我错过了一些东西。

Any help will be much appreciated.任何帮助都感激不尽。

1 个解决方案

With an anomaly detection algorithm like OneClassSVM, GaussianMixtureModel, IsolationForest etc your training setup and features will be the deciding factor in success or not.使用 OneClassSVM、GaussianMixtureModel、IsolationForest 等异常检测算法，您的训练设置和特征将成为成功与否的决定因素。

The kind of anomaly shown there will be easily detected if you transform your data to differences or rate-of-change between consecutive time-windows.如果您将数据转换为连续时间窗口之间的差异或变化率，将很容易检测到那里显示的异常类型。

什么机器学习算法适合于预测另一个时间序列？ - What machine learning algorithm is appropriate for predicting one time-series from another?

使用 scikit learn 训练机器学习模型以进行时间序列预测 - Train machine learning model with scikit learn for time-series prediction

训练时间序列数据的最佳机器学习模型是什么？ [不预测] - What is the best machine Learning model to train time series data? [ Not forecasting ]

如何检测多变量、多时间序列数据中的异常？ - How to detect anomalies in multivariate, multiple time-series data?

什么是可以在特征工程阶段使用的用于时间序列预测的简单机器学习模型？ - What is a simple machine learning model for time series prediction that can be used in the feature engineering phase?

每 15 分钟用数据创建时间序列模型 - Create Time-Series Model with data every 15minutes

机器学习预测时间序列多类信号变化 - Machine Learning to predict time-series multi-class signal changes

重整数据以进行时间序列预测机器学习的有效方法（Numpy） - Efficient way to Reshape Data for Time Series Prediction Machine Learning (Numpy)

哪种机器学习算法适合这种情况 - What Machine Learning Algorithm would be appropriate for this scenario

如何在机器学习中处理时间序列数据与其他属性？ - How to handle time series data with other attributes in machine learning?

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相关问题 什么机器学习算法适合于预测另一个时间序列？ - What machine learning algorithm is appropriate for predicting one time-series from another? 使用 scikit learn 训练机器学习模型以进行时间序列预测 - Train machine learning model with scikit learn for time-series prediction 训练时间序列数据的最佳机器学习模型是什么？ [不预测] - What is the best machine Learning model to train time series data? [ Not forecasting ] 如何检测多变量、多时间序列数据中的异常？ - How to detect anomalies in multivariate, multiple time-series data? 什么是可以在特征工程阶段使用的用于时间序列预测的简单机器学习模型？ - What is a simple machine learning model for time series prediction that can be used in the feature engineering phase? 每 15 分钟用数据创建时间序列模型 - Create Time-Series Model with data every 15minutes 机器学习预测时间序列多类信号变化 - Machine Learning to predict time-series multi-class signal changes 重整数据以进行时间序列预测机器学习的有效方法（Numpy） - Efficient way to Reshape Data for Time Series Prediction Machine Learning (Numpy) 哪种机器学习算法适合这种情况 - What Machine Learning Algorithm would be appropriate for this scenario 如何在机器学习中处理时间序列数据与其他属性？ - How to handle time series data with other attributes in machine learning?

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