# machenslab/dPCA

<https://repo.masters-masters.com/en/repos/machenslab/dPCA>

[Home](https://repo.masters-masters.com/en) › [machenslab](https://repo.masters-masters.com/en/owners/machenslab) › [dPCA](https://repo.masters-masters.com/en/repos/machenslab/dPCA)

machenslab/dPCA has 325 stars on GitHub. Its RepoMasters card: Alpha tier. An implementation of demixed Principal Component Analysis (a supervised linear…

| Field | Value |
| --- | --- |
| Owner | [machenslab](https://repo.masters-masters.com/en/owners/machenslab) |
| Stars | 325 |
| Forks | 103 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2014 |
| Topics | dimensionality-reduction, python, matlab |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [machenslab/dPCA](https://github.com/machenslab/dPCA) |

## Repository

An implementation of demixed Principal Component Analysis (a supervised linear dimensionality reduction technique)

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

## Nearby in Jupyter Notebook

- [bmurmann/ADC-survey · ★ 325 · Jupyter Notebook · Alpha](https://repo.masters-masters.com/en/repos/bmurmann/ADC-survey)
- [xbresson/CS6208\_2023 · ★ 325 · Jupyter Notebook · Alpha](https://repo.masters-masters.com/en/repos/xbresson/CS6208_2023)
- [sinanuozdemir/oreilly-ai-agents · ★ 325 · Jupyter Notebook · Alpha](https://repo.masters-masters.com/en/repos/sinanuozdemir/oreilly-ai-agents)
- [pannous/caffe-speech-recognition · ★ 325 · Jupyter Notebook · Alpha](https://repo.masters-masters.com/en/repos/pannous/caffe-speech-recognition)
- [georgesung/road\_lane\_line\_detection · ★ 325 · Jupyter Notebook · Alpha](https://repo.masters-masters.com/en/repos/georgesung/road_lane_line_detection)
- [jsleep/wav2mid · ★ 325 · Jupyter Notebook · Alpha](https://repo.masters-masters.com/en/repos/jsleep/wav2mid)

---
Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.
