recommend: Generate recommendation.

In ludovikcoba/rrecsys: Environment for Evaluating Recommender Systems

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 numeric.
pt	positive threshold, class numeric.

Value

Returns a list with suggested items for each user.

See Also

rrecsys.

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)

ludovikcoba/rrecsys documentation built on May 17, 2022, 2:33 a.m.