Dense Embedder using word2vec or GloVe

Generates dense vector embeddings using pre-trained word vectors

Public fields

dimension

Embedding dimension

model_type

Type of model being used

language

Language setting ("en" or "ml")

Methods

Public methods

• DenseEmbedder$new()

• DenseEmbedder$set_sentence_embedder()

• DenseEmbedder$embed()

• DenseEmbedder$fit()

• DenseEmbedder$clone()

---

Method new()

Create a new DenseEmbedder

Usage

DenseEmbedder$new(
  dimension = 100,
  model_path = NULL,
  model_type = "tfidf",
  sentence_embedder = NULL,
  auto_download = FALSE,
  language = "en"
)

Arguments

dimension

Vector dimension (default: 100 for word2vec, 50/100/200/300 for GloVe)

model_path

Optional path to pre-trained model file

model_type

Type: "word2vec", "glove", "glove-pretrained", or "tfidf"

sentence_embedder

Optional SentenceEmbedder object to use

auto_download

Auto-download GloVe vectors if model_type is glove-pretrained

language

Language behavior ("en" = ASCII-focused, "ml" = Unicode-aware)

---

Method set_sentence_embedder()

Set a SentenceEmbedder to use for embeddings

Usage

DenseEmbedder$set_sentence_embedder(embedder)

Arguments

embedder

SentenceEmbedder object

---

Method embed()

Embed texts to vectors

Usage

DenseEmbedder$embed(texts)

Arguments

texts

Character vector of texts

Returns

Matrix of embeddings (rows are documents)

---

Method fit()

Train embedder on corpus (for TF-IDF)

Usage

DenseEmbedder$fit(texts)

Arguments

texts

Character vector of training texts

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Method clone()

The objects of this class are cloneable with this method.

Usage

DenseEmbedder$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.