kmeans.py
357 Bytes
from sklearn.cluster import KMeans
import pickle
from abstract_clustering import AbstractClustering
class kmeans():
def __init__(self):
self.kmeans_model = None
def predict(self, features):
return self.kmeans_model.predict(features)
def load(self, model_path):
self.kmeans_model = pickle.load(open(model_path, "rb"))