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hub / github.com/TheAlgorithms/C / kMeans

Function kMeans

machine_learning/k_means_clustering.c:134–214  ·  view source on GitHub ↗

! * --K Means Algorithm-- * 1. Assign each observation to one of k groups * creating a random initial clustering * 2. Find the centroid of observations for each * cluster to form new centroids * 3. Find the centroid which is nearest for each * observation among the calculated centroids * 4. Assign the observation to its nearest centroid * to create a new clustering. * 5. R

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Callers 2

testFunction · 0.85
test2Function · 0.85

Calls 2

calculateCentroidFunction · 0.85
calculateNearstFunction · 0.85

Tested by

no test coverage detected