Files
GitMining/DataModel.hs
2015-04-05 15:45:51 +02:00

44 lines
1.2 KiB
Haskell

module DataModel where
import Data.Set (Set)
import qualified Data.Set as Set
type Count = Int
type Frequency = Double
type Confidence = Double
class Freq a where
frequency :: [ItemSet] -> a -> Frequency
data Item = Item String deriving (Eq, Ord)
instance Show Item where
show (Item s) = s --"Item " ++ s
data ItemSet = ItemSet (Set Item) deriving (Eq, Ord)
instance Show ItemSet where
show (ItemSet x) =
foldr ((\y old -> y ++ " " ++ old).show) "" (Set.toList x)
instance Freq ItemSet where
frequency table (ItemSet set) =
setCount / fromIntegral (length table) where
setCount = fromIntegral $ count table (ItemSet set)
count :: [ItemSet] -> ItemSet -> Count
count table (ItemSet set) =
length (filter isSuperSet table) where
isSuperset (ItemSet row) = set `Set.isSubsetOf` row
data Rule = Rule ItemSet ItemSet deriving (Eq)
instance Show Rule where
show (Rule a b) = show a ++ "-> " ++ show b
instance Freq Rule where
frequency table (Rule (ItemSet set1) (ItemSet set2)) = frequency table $ ItemSet (set1 `Set.union` set2)
confidence :: [ItemSet] -> Rule -> Confidence
confidence table (Rule x y) = frequency table (Rule x y) / frequency table x