import numpy as np
X = np.array([[1, 2], [2, 5], [3, 6], [8, 7], [8, 8], [7, 3]])

Initialize the model

model_ameans = ameans(max_clusters = 5, metrics = 'silhouette')

Fit on data 'X'

model_ameans.fit(X)

Predict the cluster on data 'X'

#predictions = model.predict(X)

TypeError: init() got an unexpected keyword argument 'precompute_distances'

TypeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_3964\609850703.py in
6
7 # Fit on data 'X'
----> 8 model_ameans.fit(X)
9 # Predict the cluster on data 'X'
10 #predictions = model.predict(X)

~.conda\envs\send_freq\lib\site-packages\automeans\cluster.py in fit(self, X)
207 tol=self.tol, precompute_distances=self.precompute_distances,
208 verbose=self.verbose, random_state=self.random_state,
--> 209 copy_x=self.copy_x, n_jobs=self.n_jobs, algorithm=self.algorithm)
210 labels = kmeans.fit_predict(X)
211 sil_score = silhouette_score(X, labels)

TypeError: init() got an unexpected keyword argument 'precompute_distances'