asreview.models.feature_extraction.EmbeddingIdf

class asreview.models.feature_extraction.EmbeddingIdf(*args, embedding_fp=None, random_state=None, **kwargs)

Embedding IDF feature extraction technique (embedding-idf).

This model averages the weighted word vectors of all the words in the text, in order to get a single feature vector for each text. The weights are provided by the inverse document frequencies.

Note

This feature extraction technique requires tensorflow to be installed. Use pip install tensorflow or install all optional ASReview dependencies with pip install asreview[all]

Parameters

embedding_fp (str) – Path to embedding.

Attributes

default_param	Get the default parameters of the model.
label
name
param	Get the (assigned) parameters of the model.

Methods

fit(texts)	Fit the model to the texts.
fit_transform(texts[, titles, abstracts, ...])	Fit and transform a list of texts.
full_hyper_space()
hyper_space()
transform(texts)	Transform a list of texts.