cod3licious/simec
Similarity Encoder (SimEc) Neural Network Framework for learning low dimensional similarity preserving representations
This project helps researchers analyze complex datasets by transforming raw feature vectors into a lower-dimensional representation that preserves specific similarities between data points. You input your raw data and a defined similarity metric, and it outputs a compressed, meaningful representation of your data. This is ideal for machine learning researchers or data scientists exploring new ways to understand relationships in their data.
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Use this if you need to create compact, similarity-preserving representations from high-dimensional data, especially when traditional methods struggle with noise or non-linear relationships.
Not ideal if you're looking for an out-of-the-box solution for common data analysis tasks without delving into neural network architectures or if you need a non-research-grade, production-ready system.
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Jupyter Notebook
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MIT
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Last pushed
Jun 28, 2020
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