crs: Collaborative Filtering

In radiant.model: Model Menu for Radiant: Business Analytics using R and Shiny

Collaborative Filtering

Description

Collaborative Filtering

Usage

crs(
  dataset,
  id,
  prod,
  pred,
  rate,
  data_filter = "",
  arr = "",
  rows = NULL,
  envir = parent.frame()
)

Arguments

dataset	Dataset
id	String with name of the variable containing user ids
prod	String with name of the variable with product ids
pred	Products to predict for
rate	String with name of the variable with product ratings
data_filter	Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "training == 1")
arr	Expression to arrange (sort) the data on (e.g., "color, desc(price)")
rows	Rows to select from the specified dataset
envir	Environment to extract data from

Details

See https://radiant-rstats.github.io/docs/model/crs.html for an example in Radiant

Value

A data.frame with the original data and a new column with predicted ratings

See Also

summary.crs to summarize results

plot.crs to plot results if the actual ratings are available

Examples

crs(ratings,
  id = "Users", prod = "Movies", pred = c("M6", "M7", "M8", "M9", "M10"),
  rate = "Ratings", data_filter = "training == 1"
) %>% str()

radiant.model documentation built on Oct. 16, 2023, 9:06 a.m.