Easy t-sne plotter
This is Matlab script for plotting 2 Dimensional and 3 Dimensional t-Distributed Stochastic Neighbor Embedding (t-SNE)
t-Distributed Stochastic Neighbor Embedding (t-SNE) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets. The technique can be implemented via Barnes-Hut approximations, allowing it to be applied on large real-world datasets. For more information, check this page.
How to use?
1. Clone this repository.
2. How the Dataset and label should be arranged?
i. The script requires two inputs - Data and Label.
ii. Arrangement of Data - First column should be "label name" and rest of the columns should be "features".
iii. Arrangement of Label - First column should be "label name" , which should be in the same order as
iv. Data's label names.
3. Each row in both Data and Label is a sample.
4. Replace the Data and Label in folder inputs directory with the same name.
5. Run the script tsne_example.m.
The code will generate both 2D and 3D t-sne plots. Examples of Data,Label and t-sne plots have been included with this repository.
For more detailed instructions check the website : https://rahulvigneswaran.github.io/tsne-plotter/
Issue / Want to Contribute ? :
Open a new issue (https://github.com/rahulvigneswaran/tsne-plotter/issues) or do a pull request (https://github.com/rahulvigneswaran/tsne-plotter/pulls) in case you are facing any difficulty with the code base or you want to contribute to it.
Cite As
Rahul-Vigneswaran K (2019). t-sne plotter (https://www.github.com/rahulvigneswaran/tsne-plotter), GitHub. Retrieved May 14, 2019.
MATLAB Release Compatibility
Platform Compatibility
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- AI and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
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| Version | Published | Release Notes | |
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| 1.0.4 | Updated Description |
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| 1.0.3 | Updated Description |
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| 1.0.2 | Updated Website |
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| 1.0.1 | Added Package Image |
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| 1.0.0 |
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