Pinned Repositories
category_encoders
A library of sklearn compatible categorical variable encoders
clustering-benchmark
clustering-ensemble
Removal of information from co-association matrix for clustering ensemble
ClusteringDirectionCentrality
A novel Clustering algorithm by measuring Direction Centrality (CDC) locally. It adopts a density-independent metric based on the distribution of K-nearest neighbors (KNNs) to distinguish between internal and boundary points. The boundary points generate enclosed cages to bind the connections of internal points.
CVDD
An Internal Validity Index Based on Density-Involved Distance
Deep-Semi-NMF
Theano-based implementation of Deep Semi-NMF.
EBDM
Implemented the research paper ‘A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal-Attribute Data Clustering’ by Zhang et al. and built a python package for finding a common distance matrix for the ordinal and nominal data from any kind of questionnaire data, based on entropy measures. Tested the package on multiple datasets for robustness.
gramm
Gramm is a complete data visualization toolbox for Matlab. It provides an easy to use and high-level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
SigCat
Significance-Based Categorical Data Clustering (2022) https://arxiv.org/abs/2211.03956
TestCat
Clusterability test for categorical data: A testing-based approach to assess the clusterability of categorical data (2023)
hulianyu's Repositories
hulianyu/CVDD
An Internal Validity Index Based on Density-Involved Distance
hulianyu/SigCat
Significance-Based Categorical Data Clustering (2022) https://arxiv.org/abs/2211.03956
hulianyu/category_encoders
A library of sklearn compatible categorical variable encoders
hulianyu/clustering-benchmark
hulianyu/clustering-ensemble
Removal of information from co-association matrix for clustering ensemble
hulianyu/ClusteringDirectionCentrality
A novel Clustering algorithm by measuring Direction Centrality (CDC) locally. It adopts a density-independent metric based on the distribution of K-nearest neighbors (KNNs) to distinguish between internal and boundary points. The boundary points generate enclosed cages to bind the connections of internal points.
hulianyu/Deep-Semi-NMF
Theano-based implementation of Deep Semi-NMF.
hulianyu/EBDM
Implemented the research paper ‘A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal-Attribute Data Clustering’ by Zhang et al. and built a python package for finding a common distance matrix for the ordinal and nominal data from any kind of questionnaire data, based on entropy measures. Tested the package on multiple datasets for robustness.
hulianyu/gramm
Gramm is a complete data visualization toolbox for Matlab. It provides an easy to use and high-level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
hulianyu/higher-order-organization-matlab
Experimental Matlab code for methods and some examples in "Higher-order organization of complex networks"
hulianyu/hulianyu.github.io
hulianyu/MHTC
hulianyu/TestCat
Clusterability test for categorical data: A testing-based approach to assess the clusterability of categorical data (2023)
hulianyu/hulianyu
hulianyu/Jaccard_Poisson
hulianyu/SigCM
hulianyu/SigTree