Patrick's first run of quick_start_guide.ipynb --- Number of distinct clusters (1) found smaller than n_clusters (6)

[pburauel]

In the section "Beyond the Basics: Training and predicting with just the conditional density or just with clustering"

when I run the following code:

#we'll use the same dataset2 from above 

# clusterer parameters
cluster_params = { 'n_Xclusters' : 4, 
                   'n_Yclusters' : 2 }

# create a clusterer object 
clusterer = cfl.cluster_methods.kmeans.KMeans(cluster_params) 

#train 
x_lbls, y_lbls = clusterer.train(dataset2)

error code:

ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (2). Possibly due to duplicate points in X.

I also get the same error in section "Beyond the Basics: Loading Saved Results " after I run the following code:

# this should skip cde training and just go straight to clustering
train_results = cfl_object.train(dataset0, standardize=True)

100%|██████████| 1000/1000 [00:00<00:00, 3953.24it/s] C:\Users\hftw1\AppData\Local\conda\conda\envs\tf\lib\site-packages\sklearn\cluster_kmeans.py:1122: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (6). Possibly due to duplicate points in X. return self.fit(X, sample_weight=sampleweight).labels

[111zmx666]

请问你是如何解决的