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第1版书第二章27页中,CBOW输入参数下标指向是否有问题?窗口大小为2,i=2时目标单词不应该是“在”吗?这段文字介绍和代码似乎有出入。
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请问cbow 和 cbow-na哪个会好一点
注意到cbow是通过linear去预测单词,那么词表大小最多可以是多少
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Thanks for sharing the code!
Sorry if the question is silly - my understanding of word embeddings is still premature and lack the required math background:
Should the SignalMatrix implementation f…
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I'm working on using this word2vec (I set trainer.type(NeuralNetworkType.CBOW)) to do some representing learning staff, and I wonder **how to change the vector dimensionality**
I use **getRawVector()…
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Analogous to the TransE visualization, but this time with CBOW (first order random walk sampling).
![image](https://user-images.githubusercontent.com/7738570/170890301-461f79c4-4900-49ab-9f6e-7bc3d…
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Please excuse me for asking this question here since it's not really actual _issue_ regarding gensim.
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**TL;DR:**
I'd like to know how I can get to the word vectors _before_ they are getting pro…
ghost updated
7 years ago
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http://ci.mxnet.io/blue/organizations/jenkins/GluonNLP-py3-master-gpu-integration/detail/PR-893/1/pipeline
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=================================== FAILURES ===================================
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## 一言でいうと
CBOWがSkip-gramに比べて性能が劣るのは理論面ではなく実装面の誤りとした研究。オリジナルのCBOW(とそれに忠実なgensim実装)は勾配の計算式が間違っている、具体的にはコンテキストウィンドウ内単語数で正規化していないとし、実装の修正で性能が向上するという
### 論文リンク
https://arxiv.org/abs/2012.15332
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1) Generate SenseGram models from 100 and 300 dimensinal word2vec embeddings generated from the ukWaC corpus. Use the ``uwac_2_cbow_100.text.model`` first.
2) Re-compute the unsupervised results …
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Hi, when running
```
cbow = CBOWClassifier()
trainer = dy.AdagradTrainer(cbow.model) #where mode is a parameter collection
loss = cbow.get_loss(train_set[0], True)
loss_value = loss.value()
loss…