initial_centroids = k.find_initial_centroids(n_clusters).eval() # Inital "random" guesses, based on the data. # In[10]: kmeans.plot_data(initial_centroids, data, n_samples) # In[11]: curr_centroids = tf.Variable(initial_centroids) nearest_indices = k.assign_to_nearest(curr_centroids) updated_centroids = k.update_centroids(nearest_indices) tf.global_variables_initializer().run() # Updated centroids after one iteration. # In[12]: kmeans.plot_data(updated_centroids.eval(), data, n_samples) # In[13]:
