K-Mean with OpenMP

Parallel implementation of K-Mean algorithm with OpenMP.

How to use

Compile with:

g++ -fopenmp main.cpp -o project_kmean

Execute with:

./project_kmean <input.csv> <kmean_variant> <num_threads> <k> <initialization_alg>

<input.csv> : input data file name (10 features).
<kmean_variant> : choose the clustering variant ('kmean' or 'kmedoids').
<num_threads> : number of threads.
<k> : number of clusters.
<initialization_alg> : set how to define the initial centroids ('random' or 'kmeanpp').

The algorithm returns the execution times of the different parts and the silhouette score.

Name		Name	Last commit message	Last commit date
Latest commit History 20 Commits
.idea		.idea
cmake-build-debug		cmake-build-debug
CMakeLists.txt		CMakeLists.txt
OpenMP_KMean_AMaggio.pdf		OpenMP_KMean_AMaggio.pdf
Point.h		Point.h
README.md		README.md
base_kmean.cpp		base_kmean.cpp
cluster_visual.py		cluster_visual.py
data100000_3.csv		data100000_3.csv
data10000_3.csv		data10000_3.csv
initializer.cpp		initializer.cpp
kmedoids.cpp		kmedoids.cpp
main.cpp		main.cpp
misc.cpp		misc.cpp
project.sbatch		project.sbatch
project_kmean		project_kmean