小编Shy*_*ono的帖子

我在使用 Kmeans 算法处理标签数据时遇到问题。我的测试句子得到了真实的聚类，但我没有得到真实的标签。我已经使用 numpy 将簇与 true_label_test 进行匹配，但是这个 kmeans 可以移动簇，真实标签与簇的数量不匹配。我需要帮助解决这个问题。这是我的代码

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.neighbors import KNeighborsClassifier
from sklearn.cluster import KMeans
from nltk.corpus import stopwords 
from nltk.stem.wordnet import WordNetLemmatizer
import string
import re
import numpy as np
from collections import Counter

stop = set(stopwords.words('indonesian'))
exclude = set(string.punctuation) 
lemma = WordNetLemmatizer()

# Cleaning the text sentences so that punctuation marks, stop words & digits are removed  
def clean(doc):
    stop_free = " ".join([i for i in doc.lower().split() if i not in stop]) …