https://github.com/aman-095/principal-component-analysis-pca-implementaion-from-scratch
Implemented PCA algorithm from scratch on MNIST Dataset. Visualizing the reconstructed images made and comparing them with the original image. Visualizing the residual images by subtracting the reconstructed image from the original image (for different values of Principal components). Finding the reconstruction error (pixel-wise root-mean-square) for each sample and plot them for a different number of principal components.
https://github.com/aman-095/principal-component-analysis-pca-implementaion-from-scratch
machine-learning mnist-classification mnist-dataset pca-analysis principal-component-analysis
Last synced: 4 months ago
JSON representation
Implemented PCA algorithm from scratch on MNIST Dataset. Visualizing the reconstructed images made and comparing them with the original image. Visualizing the residual images by subtracting the reconstructed image from the original image (for different values of Principal components). Finding the reconstruction error (pixel-wise root-mean-square) for each sample and plot them for a different number of principal components.
- Host: GitHub
- URL: https://github.com/aman-095/principal-component-analysis-pca-implementaion-from-scratch
- Owner: aman-095
- License: mit
- Created: 2022-08-12T18:59:23.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-08-12T19:06:19.000Z (almost 3 years ago)
- Last Synced: 2025-01-22T01:13:27.998Z (6 months ago)
- Topics: machine-learning, mnist-classification, mnist-dataset, pca-analysis, principal-component-analysis
- Language: Python
- Homepage:
- Size: 518 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- License: LICENSE