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Word Count Vectorizer#

The Word Count Vectorizer builds a vocabulary from the training samples and transforms text blobs into fixed length feature vectors. Each feature column represents a word or token from the vocabulary and the value denotes the number of times that word appears in a given document.

Interfaces: Transformer, Stateful

Data Type Compatibility: Categorical

Parameters#

#	Param	Default	Type	Description
1	max vocabulary	PHP_INT_MAX	int	The maximum number of words to encode into each document vector.
2	min document frequency	1	int	The minimum number of documents a word must appear in to be added to the vocabulary.
3	tokenizer	Word	Tokenizer	The tokenizer used to extract tokens from blobs of text.

Additional Methods#

Return an array of words in each of the vocabularies:

public vocabularies() : array

Example#

use Rubix\ML\Transformers\WordCountVectorizer;
use Rubix\ML\Other\Tokenizers\SkipGram;

$transformer = new WordCountVectorizer(10000, 3, new SkipGram());