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为什么tfidf,doc2vec你都做了stacking,而word2vec没有呢,如果加入lda的特征需要进行stacking吗
The text was updated successfully, but these errors were encountered:
为什么tfidf,doc2vec你都做了stacking,而word2vec没有呢?
TFIDF 和 Doc2Vec 都做了 Stacking,是因为这两个特征的维度太高了,不好直接输送给 XGBoost 模型。此项目中的 Word2Vec 向量维度输送给 XGBoost 模型还能够接受,另外效果上也还可以,所以没有做 Stacking。
如果加入lda的特征需要进行stacking吗?
LDA 特征输送给 XGBoost 的话,训练速度能够接受的话,可以不做 Stacking。如果基本无法训练,或者效果上不好,还是做一层 Stacking 比较好。
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为什么tfidf,doc2vec你都做了stacking,而word2vec没有呢,如果加入lda的特征需要进行stacking吗
The text was updated successfully, but these errors were encountered: