distance: Compute distance

In codymarquart/LSAfun: Applied Latent Semantic Analysis (LSA) Functions

Description

Computes distance metrics for two single words

Usage

distance(x,y,method="euclidean",tvectors=tvectors,breakdown=TRUE)

Arguments

x	A single word, given as a character of length(x) = 1
y	A single word, given as a character of length(y) = 1
method	Specifies whether to compute euclidean or cityblock metric
tvectors	the semantic space in which the computation is to be done (a numeric matrix where every row is a word vector)
breakdown	if TRUE, the function breakdown is applied to the input

Details

Computes Minkowski metrics, i.e. geometric distances between the vectors for two given words. Possible options are euclidean for the Euclidean Distance, d(x,y) = √{∑{(x-y)^2}}, and cityblock for the City Block metric, d(x,y) = ∑{|x-y|}

Value

The distance value as a numeric

Author(s)

Fritz Günther

See Also

Cosine asym

Examples

data(wonderland)

distance("alice","rabbit",method="euclidean",tvectors=wonderland)

codymarquart/LSAfun documentation built on May 13, 2019, 8:47 p.m.