oeg-upm/fuzzy-c-means
Ahmad Alobaid
fuzzy-c-means
Fuzzy c-means Clustering
Description
This implementation is based on the paper FCM: The fuzzy c-means clustering algorithm by: James C.Bezdek, Robert Ehrlich, and William Full
To run the tests
sh run_tests.shTo run the coverage
sh run_coverage.shInstall via pip
pip install fuzzycmeansHow to use it
Fit the model. This is to cluster any given data X.
X = np.array([[1, 1], [1, 2], [2, 2], [0, 0], [0, 0]])
fcm = FCM(n_clusters=3, max_iter=1)
fcm.fit(X, [0, 0, 0, 1, 2])
(Optional.) Use the model to assign new data points to existing clusters. Note that the predict function would return the membership as this a fuzzy clustering.
Y = np.array([[1, 2], [2, 2], [3, 1], [2, 1], [6, 8]])
membership = fcm.predict(Y)
Like this project
Posted Jun 12, 2023
Fuzzy c-means Clustering Libra. An implementation of the Fuzzy clustering taken from the scientific article of James C. Bezdek et at.
Likes
0
Views
1
