| Name | Version | Summary | date |
| process-improve |
0.9.95 |
Designed Experiments; Latent Variables (PCA, PLS, multivariate methods with missing data); Process Monitoring; Batch data analysis. |
2025-07-15 10:47:42 |
| hyperspy |
2.3.0 |
Multidimensional data analysis toolbox |
2025-03-02 13:36:47 |
| simpliml |
1.2.0 |
Machine Learning, Artificial Intelligence, Mathematics |
2025-01-21 07:17:12 |
| augmented-pca |
0.3.0 |
Python implementations of supervised and adversarial linear factor models. |
2024-11-08 21:07:36 |
| torch-pca |
1.0.0 |
PyTorch implementation of PCA (similar to sklearn PCA). |
2024-11-07 10:29:29 |
| adaptivepca |
1.1.3 |
An advanced PCA implementation with adaptive feature scaling and preprocessing |
2024-10-31 03:51:45 |
| prob-dim-red |
0.0.3 |
Probabilistic dimensionality reduction methods |
2024-10-22 14:19:10 |
| mafese |
0.2.0 |
Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python |
2024-06-12 15:47:19 |
| pycroscopy |
0.63.3 |
Python library for scientific analysis of microscopy data |
2024-06-05 21:32:48 |
| graphpca |
1.1.1 |
Produces a low-dimensional representation of the input graph |
2024-05-29 03:35:55 |
| disco-tif |
0.0.2 |
Geotiff processing utilities |
2024-04-17 13:31:27 |