Is there a rule for deciding dictionary size for sentiment analysis with massive datasets?
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I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?
nlp word2vec
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$begingroup$
I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?
nlp word2vec
New contributor
$endgroup$
add a comment |
$begingroup$
I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?
nlp word2vec
New contributor
$endgroup$
I will be performing sentiment analysis on fiction. I'll be working with around 300 books of 350 pages. Before performing word2vec, can I limit the dictionary size by ignoring less frequent words? If so, what is the rule for defining the size?
nlp word2vec
nlp word2vec
New contributor
New contributor
New contributor
asked 7 mins ago
Archan LagooArchan Lagoo
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Archan Lagoo is a new contributor. Be nice, and check out our Code of Conduct.
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Archan Lagoo is a new contributor. Be nice, and check out our Code of Conduct.
Archan Lagoo is a new contributor. Be nice, and check out our Code of Conduct.
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