python 异常检测模型_基于RNN时间序列的异常检测器模型在Pytorch中实现

作者：2023面试高手 | 2024-04-05 01:55:10

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异常检测模型

RNN-Time-series-Anomaly-Detection

RNN based Time-series Anomaly detector model implemented in Pytorch.

This is an implementation of RNN based time-series anomaly detector, which consists of two-stage strategy of time-series prediction and anomaly score calculation.

Requirements

Ubuntu 16.04+ (Errors reported on Windows 10. see issue. Suggesstions are welcomed.)

Python 3.5+

Pytorch 0.4.0+

Numpy

Matplotlib

Scikit-learn

Dataset

1. NYC taxi passenger count

2. Electrocardiograms (ECGs)

The ECG dataset containing a single anomaly corresponding to a pre-ventricular contraction

3. 2D gesture (video surveilance)

X Y coordinate of hand gesture in a video

4. Respiration

A patients respiration (measured by thorax extension, sampling rate 10Hz)

5. Space shuttle

Space Shuttle Marotta V

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