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SOINN is a blazing fast unsupervised clustering algorithm. This is the repo for python package soinn.
pip install soinn
python -m build
learn(data: object = None, dead_age: int = 100, lambda: int = 100, noise: float = 0.5, num_layer: int = 1) -> object
input : numpy array of shape (n, dim)
dead_age : the dead age of edges during the learning process, default 100
lamda : the number of iterations before removing noise, default 100
noise : the ratio of noise in input data, default 0.5
num_layer : the number of soinn layer, default 1
return : return a numpy array contaning all learned cendrioids, shape (n1, dim) where n1 represents the number of cendrioids.
Here is a simple code using SOINN to learn cendroids of the input data
from scipy.io import loadmat
import matplotlib.pyplot as plt
import soinn
data = loadmat("train.mat")['train']
print('Load data with shape', data.shape)
ax=plt.subplot(121)
ax.set_title('origin data')
plt.plot(data[:,0], data[:,1], '.')
clus = soinn.learn(data)
print('soinn learned clusters with shape', clus.shape)
ax=plt.subplot(122)
ax.set_title('learned cendroids')
plt.plot(clus[:,0], clus[:,1], '.')
plt.show()You can run it by:
cd demo && python demo.py
You can get the following result
