shihai1991 / kernel-density-peaksLinks
We develop the clustering approach by fast-search-and-find of density peaks which use the kernel function for mapping the input sample objects to the high dimensional feature space and amplifying the original sample objects’ characteristics, thereby researching the local density of the object attribute based on similarity measure. In order to id…
☆18Updated 9 years ago
Alternatives and similar repositories for kernel-density-peaks
Users that are interested in kernel-density-peaks are comparing it to the libraries listed below
Sorting:
- Clustering algorithms by fast search and find of density peaks☆18Updated 6 years ago
- Wang Y, Wang D, Zhang X, et al. McDPC: multi-center density peak clustering[J]. Neural Computing and Applications,2020, 1-14.☆28Updated 5 years ago
- MDPC+：Clustering by fast detection of main density peaks within a peak digraph☆10Updated 2 years ago
- Comparison among K-Means, DBSCAN and Density Peak☆25Updated 6 years ago
- Clustering by fast search and find of density peaks☆24Updated 11 years ago
- The matlab code for the paper 'GoDec+: Fast and Robust Low-Rank Matrix Decomposition Based on Maximum Correntropy'☆16Updated 8 years ago
- The codes的K-means，FCM，谱聚类，DBSCAN，AP（AffinityPropagation），DPC聚类算法比较☆158Updated 8 years ago
- Density Peaks Clustering Based on Density Backbone and Fuzzy Neighborhood☆32Updated 5 years ago
- The code for the paper "Spatio-Temporal Structured Sparse Regression With Hierarchical Gaussian Process Priors" by Danil Kuzin, Olga Isup…☆13Updated 7 years ago
- A MATLAB toolbox for classifier: Version 1.0.7☆89Updated 2 years ago
- Several state-of-the-art fuzzy clustering algorithms, including Fuzzy c-means clustering, fuzzy subspace clustering and maximum entropy c…☆33Updated 5 years ago
- Sparce Subspace Clustering (SSC) is a subspace clustering algorithm that uses sparse vector representation, convex optimization, and spec…☆45Updated 9 years ago
- Matlab implementation of the Bayesian Fuzzy Clustering algorithms. See related paper, doi: 10.1109/TFUZZ.2014.2370676☆25Updated 6 years ago
- Feature fusion using Discriminant Correlation Analysis (DCA)☆65Updated 5 years ago
- ☆26Updated 8 years ago
- This provides an MATLAB code implementation for the paper "Low-rank and Sparse Matrix Decomposition via the Truncated Nuclear Norm and a …☆31Updated 7 years ago
- mainly aimed at scalable subspace clustering☆11Updated 8 years ago
- A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning☆38Updated 5 years ago
- Performing Foreground Detection in videos using RPCA with ADMM algorithm☆18Updated 5 years ago
- Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approa…☆73Updated 4 years ago
- Dynamic Graph-Based Label Propagation for Density Peaks Clustering☆44Updated 3 years ago
- Iteratively Reweighted Nuclear Norm for Nonconvex Nonsmooth Low-rank Minimization☆25Updated 4 years ago
- Regularized K-SVD Algorithm☆49Updated 8 years ago
- Bayesian Group-sparse Compressed Sensing Toolbox (FG 2015)☆44Updated 7 years ago
- Discriminative Feature Selection via A Structured Sparse Subspace Learning Module☆12Updated 3 years ago
- Scripts for the paper: 2DPCA with L1-norm for simultaneously robust and sparse modelling.☆17Updated 6 years ago
- This packaged is an implementation of our paper "Robust Denoising of Piece-Wise Smooth Manifolds", ICASSP 2018 The algorithm creates an …☆15Updated 6 years ago
- A MATLAB library for sparse representation problems☆105Updated 3 years ago
- Band selection and classification of hyperspectral images using Multi-objective Genetic Algorithms☆14Updated 6 years ago
- 目前多流形学习算法matlab代码☆13Updated 7 years ago