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 asreview[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.