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发现这块逻辑存在问题,
words_count = Counter(words)
words = [w for w in words if words_count[w] > 50]
In [19]:
vocab = set(words)
vocab_to_int = {w: c for c, w in enumerate(vocab)}
int_to_vocab = …
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Carbon footprint is a useful metric to output.
Tools such as the following coupled with location data associated with nodes could be useful:
https://github.com/Green-Software-Foundation/carbon-aware…
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Any chance this can get bumped to Craft 5 soon? We use this to convert pounds to grams for a UPS shipping integration (to calculate shipping cost). Business critical, so we'd otherwise need to rewrite…
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The goal of the common grams filter is to speed up phrase queries on common words. For that purpose, it adds shingles to the token stream when it encounters common words (as provided in a list). Then …
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It seems that n-grams are very usefull, in Russian there are many rare words that are excluded from spellcheck dictionaries to provide more matches for possible errors (like rare.koi file from http:/…
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I have a training data where each token is a word and I've already extracted a few features like NER, POS and CHUNK for each token. But I have a problem when I try to extract character n-grams feature…
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Given https://github.com/giacbrd/ShallowLearn/issues/1, implementing n-grams of words
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`n-grams` can considerably accelerate `PhraseQuery`.
Let's say one is trying to search `The quest for the holy grail`...
A phrase query will compute the intersection of the posting list associate…
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
An article-based feature with guidance that includes an image, item name, grams, protein c…
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Allowing tokenize documents with character n-grams would be useful.