我想使用 word2vec 执行文本分类。我得到了词向量。
ls = []
sentences = lines.split(".")
for i in sentences:
ls.append(i.split())
model = Word2Vec(ls, min_count=1, size = 4)
words = list(model.wv.vocab)
print(words)
vectors = []
for word in words:
vectors.append(model[word].tolist())
data = np.array(vectors)
data
输出：
array([[ 0.00933912, 0.07960335, -0.04559333, 0.10600036],
[ 0.10576613, 0.07267512, -0.10718666, -0.00804013],
[ 0.09459028, -0.09901826, -0.07074171, -0.12022413],
[-0.09893986, 0.01500741, -0.04796079, -0.04447284],
[ 0.04403428, -0.07966098, -0.06460238, -0.07369237],
[ 0.09352681, -0.03864434, -0.01743148, 0.11251986],.....])
我如何进行分类（产品和非产品）？