lsp-python is a lightweight implementation of the Least Square Projection (LSP) dimensionality reduction technique using a sklearn style API.
Project description
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pyLSP
pyLSP is a lightweight python implementation of the Least Square Projection (LSP) dimensionality reduction technique using sklearn style API.
The implementation is based on the paper "Least Square Projection: A Fast High-Precision Multidimensional Projection Technique and Its Application to Document Mapping", which can be cited using:
@ARTICLE{4378370,
author={Paulovich, Fernando V. and Nonato, Luis G. and Minghim, Rosane and Levkowitz, Haim},
journal={IEEE Transactions on Visualization and Computer Graphics},
title={Least Square Projection: A Fast High-Precision Multidimensional Projection Technique and Its Application to Document Mapping},
year={2008},
volume={14},
number={3},
pages={564-575},
keywords={Least squares methods;Multidimensional systems;Data visualization;Least squares approximation;Data analysis;Computational geometry;Testing;Text processing;Data mining;Demography;Multivariate visualization;Data and knowledge visualization;Information visualization;Multivariate visualization;Data and knowledge visualization;Information visualization},
doi={10.1109/TVCG.2007.70443}}
A small working example can be found in tests/iris_example.py and tests/digits_example.py.
