-- Hoogle documentation, generated by Haddock
-- See Hoogle, http://www.haskell.org/hoogle/


-- | A very simple implementation of decision trees for discrete attributes.
--   
--   A very simple implementation of decision trees, built with ID3. You
--   can use it to classify data with a set of discrete attributes.
@package DecisionTree
@version 0.0


-- | This module provides a very simple implementation of a decisiontree.
--   It is "optimized" for readability, not so much for performance. I
--   doubt it can be used for real (=huge) datasets, but it should be ok
--   for a couple of hundred (thousand?) items.
--   
--   You are encouraged to have a look at the source
--   
--   It is build (for now) using the ID3 algorithm (or at least something
--   closely resembling that). That means the attributes you choose must
--   have a finite set of possible values.
module Data.DecisionTree

-- | Build a DecisionTree from the given Trainingset
build :: (Ord a, Ord b) => [Attribute a] -> [PreLabeled a b] -> DecisionTree a b

-- | Decide which label belongs to this Datum
decide :: (Eq a) => DecisionTree a b -> Datum a -> b

-- | Things we want to find labels for
data Datum a
D :: String -> [(Attribute a, a)] -> Datum a

-- | They have names
dName :: Datum a -> String

-- | and attributes
attributes :: Datum a -> [(Attribute a, a)]
type PreLabeled a b = (b, Datum a)

-- | A Datum has Attributes
data Attribute a
A :: String -> [a] -> Attribute a

-- | Attributes have a name
aName :: Attribute a -> String

-- | and a set of possible values
possibleValues :: Attribute a -> [a]

-- | The type for our DecisionTree
data DecisionTree a b
instance (Show a) => Show (Datum a)
instance Show (Attribute a)
instance Eq (Attribute a)
instance (Show a, Show b) => Show (DecisionTree a b)