bootstrap_contrast: Bootstrap similarity and ratio computations

In conText: 'a la Carte' on Text (ConText) Embedding Regression

Bootstrap similarity and ratio computations

Description

Bootstrap similarity and ratio computations

Usage

bootstrap_contrast(
  target_embeddings1 = NULL,
  target_embeddings2 = NULL,
  pre_trained = NULL,
  candidates = NULL,
  norm = NULL
)

Arguments

target_embeddings1	ALC embeddings for group 1
target_embeddings2	ALC embeddings for group 2
pre_trained	a V x D matrix of numeric values - pretrained embeddings with V = size of vocabulary and D = embedding dimensions
candidates	character vector defining the candidates for nearest neighbors - e.g. output from get_local_vocab
norm	character = c("l2", "none") - set to 'l2' for cosine similarity and to 'none' for inner product (see ?sim2 in text2vec)

Value

a list with three elements, nns for group 1, nns for group 2 and nns_ratio comparing with ratios of similarities between the two groups

conText documentation built on Feb. 16, 2023, 7:32 p.m.