widyr (version 0.1.5)

widely_svd: Turn into a wide matrix, perform SVD, return to tidy form

Description

This is useful for dimensionality reduction of items, especially when setting a lower nv.

Usage

widely_svd(tbl, item, feature, value, nv = NULL, weight_d = FALSE, ...)
widely_svd_(tbl, item, feature, value, nv = NULL, weight_d = FALSE, ...)

Value

A tbl_df with three columns. The first is retained from the item input, then dimension and value. Each row represents one principal component value.

Arguments

tbl

Table

item

Item to perform dimensionality reduction on; will end up in item column

feature

Column describing the feature that links one item to others.

value

Value

nv

Optional; the number of principal components to estimate. Recommended for matrices with many features.

weight_d

Whether to multiply each value by the d principal component.

...

Extra arguments passed to svd (if nv is NULL) or irlba (if nv is given)

Examples

library(dplyr)
library(gapminder)

# principal components driving change
gapminder_svd <- gapminder %>%
  widely_svd(country, year, lifeExp)

gapminder_svd

# compare SVDs, join with other data
library(ggplot2)
library(tidyr)

gapminder_svd %>%
  spread(dimension, value) %>%
  inner_join(distinct(gapminder, country, continent), by = "country") %>%
  ggplot(aes(`1`, `2`, label = country)) +
  geom_point(aes(color = continent)) +
  geom_text(vjust = 1, hjust = 1)