| title | n_gram: n_gram |
|---|---|
| description | Extracts NGrams from text and convert them to vector using dictionary. |
| keywords | N-Grams |
| author | WilliamDAssafMSFT |
| ms.author | wiassaf |
| manager | cgronlun |
| ms.date | 07/15/2019 |
| ms.topic | reference |
| ms.prod | sql |
| ms.technology | machine-learning-services |
| ms.service | |
| ms.assetid | |
| ROBOTS | |
| audience | |
| ms.devlang | Python |
| ms.reviewer | |
| ms.suite | |
| ms.tgt_pltfrm | |
| ms.custom | |
| monikerRange | >=sql-server-2017||>=sql-server-linux-ver15 |
microsoftml.n_gram(ngram_length: numbers.Real = 1,
skip_length: numbers.Real = 0, all_lengths: bool = True,
max_num_terms: list = [10000000], weighting: str = 'Tf')
Extracts NGrams from text and convert them to vector using dictionary.
Ngram length (settings).
Maximum number of tokens to skip when constructing an ngram (settings).
Whether to include all ngram lengths up to NgramLength or only NgramLength (settings).
Maximum number of ngrams to store in the dictionary (settings).
The weighting criteria (settings).