Python Implementation of KMeans Clustering algorithm based on Euclidean distance.
Accepts Pandas DataFrame.
Api is similar to Scikit-learn.
from KMeansClustering import KMeans as KMn
X, y = make_blobs(n_samples=100, centers=5, n_features=20, random_state=0)
sample = pd.DataFrame(X)
kmn = KMn(5)
kmn.fit(sample)
print(kmn.predict(X))
print("Labels :{}".format(kmn.labels))
print("Centers :{}".format(kmn.centers))
print("Number of iteration = {}".format(kmn.n_iteration))