WEFE API

This is the documentation of the API of WEFE.

WordEmbeddingModel

WordEmbeddingModel(model[, model_name, ...])

A container for Word Embedding pre-trained models.

Query

Query(target_sets, attribute_sets[, ...])

A container for attribute and target word sets.

BaseMetric

metrics.BaseMetric()

A base class to implement any metric following the framework described by WEFE.

WEAT

WEAT()

A implementation of Word Embedding Association Test (WEAT).

RND

RND()

A implementation of Relative Norm Distance (RND).

RNSB

RNSB()

A implementation of Relative Relative Negative Sentiment Bias (RNSB).

ECT

ECT()

An implementation of the Embedding Coherence Test.

RIPA

RIPA()

An implementation of the Relational Inner Product Association Test, proposed by [1][2].

Dataloaders

The following functions allow us to load word sets used in previous works.

Load BingLiu

load_bingliu()

Load the bing-liu sentiment lexicon.

Fetch Debias Multiclass Word sets

fetch_debias_multiclass()

Fetch the word sets used in the paper Black Is To Criminals Caucasian Is To Police: Detecting And Removing Multiclass Bias In Word Embeddings.

Fetch Debias Word Embedding Word Sets

fetch_debiaswe()

Fetch the word sets used in the paper Man is to Computer Programmer as Woman is to Homemaker? from the source.

Fetch Embedding Dynamic Stereotypes Word Sets

fetch_eds([occupations_year, ...])

Fetch the word sets used in the experiments of the work Word Embeddings *Quantify 100 Years Of Gender And Ethnic Stereotypes.

Load Word Embedding Association Test Word Sets

load_weat()

Load the word sets used in the paper Semantics Derived Automatically From Language Corpora Contain Human-Like Biases.