recommend {rrecsys} | R Documentation |
Generate recommendation.
Description
This method generates top-n recommendations based on a model that has been trained before. Two main methods: recommendHPR, recommendMF. The first method recommends the highest predicted ratings on a user. Instead recommendMF (currently available only for IBKNN and UBKNN), recommends the most frequent item in the user's neighborhood.
Usage
recommendHPR(model, topN = 3)
recommendMF(model, topN = 3, pt)
Arguments
model |
the trained model of any algorithm. |
topN |
number of items to be recommended per user, class |
pt |
positive threshold, class |
Value
Returns a list with suggested items for each user.
See Also
Examples
myratings <- matrix(sample(c(0:5), size = 200, replace = TRUE,
prob = c(.6,.08,.08,.08,.08,.08)), nrow = 20, byrow = TRUE)
myratings <- defineData(myratings)
r <- rrecsys(myratings, alg = "FunkSVD", k = 2)
rec <- recommendHPR(r)
[Package rrecsys version 0.9.7.3.1 Index]