proxy.golang.org : github.com/wenjiedu/pypots
A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values
Registry
-
Source
- Documentation
- JSON
- codemeta.json
purl: pkg:golang/github.com/wenjiedu/pypots
Keywords:
anomaly-detection
, classification
, clustering
, data-analysis
, data-mining
, data-science
, deep-learning
, forecasting
, generation
, imputation
, machine-learning
, missing-values
, neural-networks
, pytorch
, time-series
License: BSD-3-Clause
Latest release: about 1 year ago
First release: over 3 years ago
Stars: 1,728 on GitHub
Forks: 164 on GitHub
Total Commits: 886
Committers: 14
Average commits per author: 63.286
Development Distribution Score (DDS): 0.024
More commit stats: commits.ecosyste.ms
See more repository details: repos.ecosyste.ms
Funding links: https://github.com/sponsors/WenjieDu
Last synced: 24 days ago