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Holder for SISAP 2020

C++ 85.73% Python 2.28% Makefile 1.04% Jupyter Notebook 8.66% Dockerfile 0.96% Shell 1.32%

elkanopt's Introduction

Placeholder for SISAP 2020 paper

Yu et al. Using a Set of Triangle Inequalities to Accelerate K-means Clustering, SISAP 2020

##File structures:

.
├── Fast-elkan                       # Placeholder for outputs
│   ├── Makefile          
│   ├── Readme.md    # Detailed readme for the framework
|   ├── src                # source code (*.cpp)
│   └── include        # header (*.h)
├── datasets                    # Placeholder for dataset files    
├── datapreprocessing.py     # Preprocessing python script
└── README.md

The preprocessing python script works for the following tested datasets at least:

Usage of preprocessing script:

Usage: python dataPreprocessing.py <flag> <path/of/inputDataset> <path/of/outputDataset> <name>, flag 0 for LIBSVM; 1 for UCI repository 
for example: python dataPreprocessing.py 0 datasets/ datasets/ skin_nonskin

elkanopt's People

Contributors

khchentw avatar nilhoel1 avatar

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