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Built-in distance functions

Source: R/dist_fns_list.R
dist_fns.Rd

These functions can be used when building a metasnf distance functions list. Each function converts a data frame into to a distance matrix.

Usage

euclidean_distance(df, weights_row)

gower_distance(df, weights_row)

sn_euclidean_distance(df, weights_row)

sew_euclidean_distance(df, weights_row)

hamming_distance(df, weights_row)

Arguments

df

Data frame containing at least 1 data column

weights_row

Single-row data frame where the column names contain the column names in df and the row contains the corresponding weights_row.

Value

A matrix class object containing pairwise distances.

Details

Functions that work for numeric data:

  • euclidean_distance: typical Euclidean distance

  • sn_euclidean_distance: Data frame is first standardized and normalized before typical Euclidean distance is applied

  • siw_euclidean_distance: Squared (including weights) Euclidean distance, where the weights are also squared

  • sew_euclidean_distance: Squared (excluding weights) Euclidean distance, where the weights are not also squared

Functions that work for binary data:

  • hamming_distance: typical Hamming distance

Functions that work for any type of data:

  • gower_distance: Gower distance (cluster::daisy)