radiant.model (version 1.6.7)

crs: Collaborative Filtering

Description

Collaborative Filtering

Usage

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

Value

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

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

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()