Feature Selection by Optimized LASSO algorithm
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Updated
May 3, 2017 - MATLAB
Feature Selection by Optimized LASSO algorithm
CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations
Statistics for high-dimensional data (homogeneity, sphericity, independence, spherical uniformity)
a GUI-based Interactive Multi-dimensional extensiBLe Visualization toolbox for Matlab
MATLAB code for Unsupervised Feature Selection with Multi-Subspace Randomization and Collaboration (SRCFS) (KBS 2019)
MWPCR-with-Matlab
[IEEE TSP 2024] "OPIT: A Simple but Effective Sparse Subspace Tracking". In IEEE Transactions on Signal Process. 2024
Code for the paper E. Raninen, D. E. Tyler and E. Ollila, "Linear pooling of sample covariance matrices," in IEEE Transactions on Signal Processing, Vol 70, pp. 659-672, 2022, doi: 10.1109/TSP.2021.3139207.
An advanced version of K-Means using Particle swarm optimization for clustering of high dimensional data sets, which converges faster to the optimal solution.
High-Dimensional Similarity Learning
An Efficeint and Fast Wrapper-based High-dimensional Feature Selection(SIFE) in MATLAB
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