---
title: "n_gram_hash: n_gram_hash"
description: "Extracts NGrams from text and convert them to vector using hashing trick."
author: VanMSFT
ms.author: vanto
ms.date: 07/15/2019
ms.service: sql
ms.subservice: "machine-learning-services"
ms.topic: "reference"
keywords:
  - N-Grams
  - hash
ms.devlang: python
monikerRange: ">=sql-server-2017||>=sql-server-linux-ver15"
---
# *microsoftml.n_gram_hash*: Converts text into features using hashed n-grams





## Usage



```
microsoftml.n_gram_hash(hash_bits: numbers.Real = 16,
    ngram_length: numbers.Real = 1, skip_length: numbers.Real = 0,
    all_lengths: bool = True, seed: numbers.Real = 314489979,
    ordered: bool = True, invert_hash: numbers.Real = 0)
```





## Description

Extracts NGrams from text and convert them to vector using hashing trick.


## Arguments


### hash_bits

Number of bits to hash into. Must be between 1 and 30, inclusive. (settings).


### ngram_length

Ngram length (settings).


### skip_length

Maximum number of tokens to skip when constructing an ngram (settings).


### all_lengths

Whether to include all ngram lengths up to ngramLength or only ngramLength (settings).


### seed

Hashing seed (settings).


### ordered

Whether the position of each source column should be included in the hash (when there are multiple source columns). (settings).


### invert_hash

Limit the number of keys used to generate the slot name to this many. 0 means no invert hashing, -1 means no limit. (settings).


## See also

[n_gram](n-gram.md),
[featurize_text](featurize-text.md)