utils: Utilities
In matloff/rectools: Advanced Recommender System
ratingness,covratingness,getML100K,getInstEval R Documentation
Utilities
Description
Miscellaneous utility functions.
Usage
ratingness(ratingsIn,splitCol)
covratingness(ratingsIn,splitCol)
getInstEval()
Arguments
ratingsIn
Input data frame. Within-row format is UserID,
ItemID, Rating and optional covariates.
splitCol
Column to count ratings for – 1 for user ratings, 2
for item ratings.
Details
The InstEval and 100K MovieLens datasets serve as examples and
testbeds for many methods in this package. Since each requires some
amount of setup, we encapsulate the setup operations in the
getInstEval and getML100K functions.
The fact that some users rate more items may itself be useful as a
predictor. Frequent rates, for instance, may be more liberal in
their ratings, so this variable may be important to include as a
covariate.
A typical usage is to call covratingness and then append the
result to the input data frame.
Author(s)
Norm Matloff
Examples
rtin <- data.frame(uid = c(1,3,2,1,2),itemid = c(1,2,1,2,2), rats=c(2,5,3,5,1))
ratingness(rtin,1)
# returns (2,2,1), meaning that user 1 submitted 2 ratings, etc.
> covratingness(rtin,1)
# returns a 5-element vector, corresponding to the 5 rows of rtin
rtin$nrats <- covratingness(rtin,1)
# now usable as a predictor
matloff/rectools documentation built on March 31, 2022, 12:09 p.m.
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| ratingness,covratingness,getML100K,getInstEval | R Documentation |
Utilities
Description
Miscellaneous utility functions.
Usage
ratingness(ratingsIn,splitCol) covratingness(ratingsIn,splitCol) getInstEval()
Arguments
ratingsIn |
Input data frame. Within-row format is UserID, ItemID, Rating and optional covariates. |
splitCol |
Column to count ratings for – 1 for user ratings, 2 for item ratings. |
Details
The InstEval and 100K MovieLens datasets serve as examples and
testbeds for many methods in this package. Since each requires some
amount of setup, we encapsulate the setup operations in the
getInstEval and getML100K functions.
The fact that some users rate more items may itself be useful as a predictor. Frequent rates, for instance, may be more liberal in their ratings, so this variable may be important to include as a covariate.
A typical usage is to call covratingness and then append the
result to the input data frame.
Author(s)
Norm Matloff
Examples
rtin <- data.frame(uid = c(1,3,2,1,2),itemid = c(1,2,1,2,2), rats=c(2,5,3,5,1)) ratingness(rtin,1) # returns (2,2,1), meaning that user 1 submitted 2 ratings, etc. > covratingness(rtin,1) # returns a 5-element vector, corresponding to the 5 rows of rtin rtin$nrats <- covratingness(rtin,1) # now usable as a predictor
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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