High Dimensional Data
Showing 7 of 7 projects
A C++ library for fast approximate nearest neighbor searches in high-dimensional spaces with automatic algorithm selection.
A fast implementation of random forests for classification, regression, and survival analysis, optimized for high-dimensional data.
Official implementation of the LargeVis algorithm for visualizing large-scale, high-dimensional data and networks.
A C++ toolbox providing multiple locality-sensitive hashing algorithms for large-scale approximate nearest neighbor search, with Python and MATLAB bindings.
A fast feature selection algorithm for tree-based models like XGBoost, designed to outperform Boruta in speed and performance.
A Ruby gem providing high-speed approximate nearest neighbor search using the NGT library.
An R package for processing and analyzing high-dimensional morphological profiling data from image-based cell biology.
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