Safe Haskell | Safe-Infered |
---|

Scoring functions commonly used for evaluation of NLP
systems. Most functions in this module work on lists, but some take
a precomputed table of `Counts`

. This will give a speedup if you
want to compute multiple scores on the same data. For example to
compute the Mutual Information, Variation of Information and the
Adujusted Rand Index on the same pair of clusterings:

`>>>`

`let cs = counts $ zip "abcabc" "abaaba"`

`>>>`

`mapM_ (print . ($ cs)) [mi, ari, vi]`

- accuracy :: (Eq a, Fractional n) => [a] -> [a] -> n
- recipRank :: (Eq a, Fractional n) => a -> [a] -> n
- avgPrecision :: (Fractional n, Ord a) => Set a -> [a] -> n
- ari :: (Ord a, Ord b) => Counts a b -> Double
- mi :: (Ord a, Ord b) => Counts a b -> Double
- vi :: (Ord a, Ord b) => Counts a b -> Double
- type Count = Double
- data Counts a b
- sum :: Num a => [a] -> a
- mean :: (Fractional n, Real a) => [a] -> n
- jaccard :: (Fractional n, Ord a) => Set a -> Set a -> n
- entropy :: [Count] -> Double

# Scores for classification and ranking

accuracy :: (Eq a, Fractional n) => [a] -> [a] -> nSource

Accuracy: the proportion of elements in the first list equal to elements at corresponding positions in second list. Lists should be of equal lengths.

recipRank :: (Eq a, Fractional n) => a -> [a] -> nSource

Reciprocal rank: the reciprocal of the rank at which the first arguments occurs in the list given as the second argument.

avgPrecision :: (Fractional n, Ord a) => Set a -> [a] -> nSource

Average precision. http://en.wikipedia.org/wiki/Information_retrieval#Average_precision

# Scores for clustering

ari :: (Ord a, Ord b) => Counts a b -> DoubleSource

Adjusted Rand Index: http://en.wikipedia.org/wiki/Rand_index

mi :: (Ord a, Ord b) => Counts a b -> DoubleSource

Mutual information: MI(X,Y) = H(X) - H(X|Y) = H(Y) - H(Y|X). Also known as information gain.

vi :: (Ord a, Ord b) => Counts a b -> DoubleSource

Variation of information: VI(X,Y) = H(X) + H(Y) - 2 MI(X,Y)

# Auxiliary types and functions

mean :: (Fractional n, Real a) => [a] -> nSource

The mean of a list of numbers.