| Name | Version | Summary | date |
| matrixprofile |
1.1.10 |
An open source time series data mining library based on Matrix Profile algorithms. |
2021-01-16 12:57:34 |
| isotree |
0.1.28.post1 |
Isolation-Based Outlier Detection, Distance, and NA imputation |
2021-01-13 19:43:21 |
| outliertree |
1.3.4 |
Explainable outlier detection through smart decision tree conditioning |
2021-01-09 16:58:33 |
| aakr |
0.0.1a0 |
Implementation of Auto Associative Kernel Regression (AAKR) |
2020-12-29 00:29:43 |
| Anomaly-Model |
1.8.0 |
import method for anomaly detection |
2020-10-26 14:40:32 |
| pyanomaly |
0.0.2.4 |
Time series anomaly detection in Python |
2020-09-30 03:19:33 |
| deepant |
0.0.1 |
DeepAnT anomaly detection implementation in pytorch |
2020-09-03 12:59:57 |
| torchvision4ad |
0.1.1 |
torchvision for anomaly detection |
2020-07-20 01:36:15 |
| anomaly-detection-framework |
0.0.19 |
Anomaly Detection Framework allows us to calculate Anomalities on any Time - Series Data Sets. It has an interface which is easy to manage to train - predict with given dataset. |
2020-06-25 23:52:19 |
| PyNomaly |
0.1.8 |
A Python 3 implementation of LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1]. |
2018-04-03 03:09:53 |
| anomaly-detection |
1.0.0 |
An Anomaly Detection Package |
2018-01-03 17:01:09 |
| lsanomaly |
0.1.3 |
Least squares anomaly detection. |
2016-08-22 22:13:17 |