Safe Haskell	None
Language	Haskell2010

Numeric.Recommender.ALS

Synopsis

data ALSParams = ALSParams {
- lambda :: Double
- alpha :: Double
- seed :: Int
- nFactors :: Int
- parChunk :: Int
}
data ALSResult = ALSResult {
- cost :: Double
- itemFeature :: !(Matrix Double)
- userFeature :: !(Matrix Double)
}
data ALSModel u i = ALSModel {
- encodeUser :: u -> Maybe Int
- decodeUser :: Int -> u
- encodeItem :: i -> Maybe Int
- decodeItem :: Int -> i
- pairs :: [(Int, Int)]
- results :: [ALSResult]
}
buildModel :: (Functor f, Foldable f) => ALSParams -> (u -> Int) -> (Int -> u) -> (i -> Int) -> (Int -> i) -> f (u, i) -> ALSModel u i
recommend :: ALSModel u i -> Int -> IntMap [(i, Bool)]

Documentation

data ALSParams Source #

Constructors

ALSParams
Fields lambda :: Double Training speed alpha :: Double Weight multiplier seed :: Int RNG seed nFactors :: Int Hidden features dimension parChunk :: Int Chunk size for parallelization

Instances

Show ALSParams Source #
Instance details Defined in Numeric.Recommender.ALS Methods showsPrec :: Int -> ALSParams -> ShowS # show :: ALSParams -> String # showList :: [ALSParams] -> ShowS #
Default ALSParams Source #
Instance details Defined in Numeric.Recommender.ALS Methods def :: ALSParams #

data ALSResult Source #

Constructors

ALSResult
Fields cost :: Double itemFeature :: !(Matrix Double) userFeature :: !(Matrix Double)

data ALSModel u i Source #

Constructors

ALSModel
Fields encodeUser :: u -> Maybe Int User to dense representation decodeUser :: Int -> u User from dense representation encodeItem :: i -> Maybe Int Item to dense representation decodeItem :: Int -> i Item from dense representation \| Internal representation of the input data pairs pairs :: [(Int, Int)] results :: [ALSResult] Results as further iterations of the algorithm

buildModel Source #

Arguments

:: (Functor f, Foldable f)
=> ALSParams
-> (u -> Int)
-> (Int -> u)
-> (i -> Int)
-> (Int -> i)
-> f (u, i)	User-item pairs
-> ALSModel u i

Build recommendations based on users' unrated item choices.

Takes conversion functions to/from Int representation for user supplied data types. Use id if you're already based on them.

The implementation follows the one in the recommenderlab library in CRAN. For further details, see "Large-scale Parallel Collaborative Filtering for the Netflix Prize" by Yunhong Zhou, Dennis Wilkinson, Robert Schreiber and Rong Pan.

recommend Source #

Arguments

:: ALSModel u i
-> Int	Iterations
-> IntMap [(i, Bool)]