https://github.com/mpolinowski/manifold-learning-for-image-segmentation

Use Manifold Learning, Mapping and Discriminant Analysis to Visualize Image Datasets
https://github.com/mpolinowski/manifold-learning-for-image-segmentation

fisher-discriminant-analysis image-segmentation isomap locally-linear-embedding principal-component-analysis python scikit-learn

Last synced: 8 days ago
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Use Manifold Learning, Mapping and Discriminant Analysis to Visualize Image Datasets

• Host: GitHub
• URL: https://github.com/mpolinowski/manifold-learning-for-image-segmentation
• Owner: mpolinowski
• Created: 2023-04-15T13:13:52.000Z (almost 2 years ago)
• Default Branch: master
• Last Pushed: 2023-04-15T13:54:39.000Z (almost 2 years ago)
• Last Synced: 2024-11-30T11:12:04.481Z (2 months ago)
• Topics: fisher-discriminant-analysis, image-segmentation, isomap, locally-linear-embedding, principal-component-analysis, python, scikit-learn
• Language: Jupyter Notebook
• Homepage: https://mpolinowski.github.io/docs/IoT-and-Machine-Learning/ML/2023-04-14-manifold-learning-for-image-segmentation/2023-04-14/
• Size: 4.34 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Dimensionality Reduction for Image Segmentation

## Use Manifold Learning, Mapping and Discriminant Analysis to Visualize Image Datasets

I will use different techniques to embed the digits dataset and plot the projection of the original data onto each embedding. This allows us to check whether or digits are grouped together in the embedding space, or scattered randomly across it to evaluate if we can classify them into groups.

1. [Locally Linear Embedding](https://github.com/mpolinowski/manifold-learning-for-image-segmentation/tree/master/01-Locally_Linear_Embedding)

    * [Locally Linear Embedding (LLE) for Tabular Datasets](https://mpolinowski.github.io/docs/IoT-and-Machine-Learning/ML/2023-04-11-locally-linear-embedding/2023-04-11)

2. [Principal Component Analysis](https://github.com/mpolinowski/manifold-learning-for-image-segmentation/tree/master/02-Principal_Component_Analysis)

    * [Principal Component Analysis (PCA) for Tabular Datasets](https://mpolinowski.github.io/docs/IoT-and-Machine-Learning/ML/2023-04-09-principal-component-analysis/2023-04-09)

3. [Fisher Discriminant Analysis](https://github.com/mpolinowski/manifold-learning-for-image-segmentation/tree/master/03-Fisher_Discriminant_Analysis)

    * [Fisher Linear Discriminant Analysis (LDA) for Tabular Datasets](https://mpolinowski.github.io/docs/IoT-and-Machine-Learning/ML/2023-04-13-fisher-discriminant-analysis/2023-04-13)

4. [Isometric Mapping](https://github.com/mpolinowski/manifold-learning-for-image-segmentation/tree/master/04-Isometric_Mapping)

    * [Isometric Mapping (ISOMAP) for Tabular Datasets](https://mpolinowski.github.io/docs/IoT-and-Machine-Learning/ML/2023-04-13-isometric-mapping/2023-04-13)