从这里查看这段代码
import numpy as np
from kmodes.kmodes import KModes
# random categorical data
data = np.random.choice(20, (100, 10))
km = KModes(n_clusters=4, init='Huang', n_init=5, verbose=1)
clusters = km.fit_predict(data)
# Print the cluster centroids
print(km.cluster_centroids_)有没有人碰巧知道如何保存“集群模型”并将其应用于新的数据?或者换句话说,集群以前看不见的数据?谢谢。
发布于 2022-02-10 16:04:40
您可以在此任务中使用pickle。
import pickle
with open('cluster_model.pickle', 'wb') as n:
pickle.dump(km, n)当您想要在新数据上使用它时,只需:
with open('cluster_model.pickle', 'rb') as f:
km = pickle.load(f)
# If your new data is called "new_data", you can:
new_clusters = km.predict(new_data)https://stackoverflow.com/questions/71067481
复制相似问题