Data.HInduce.Classifier

In machine learning and pattern recognition, classification refers to an algorithmic procedure for assigning a given piece of input data into one of a given number of categories. An example would be assigning a given email into spam or non-spam classes or assigning a diagnosis to a given patient as described by observed characteristics of the patient (gender, blood pressure, presence or absence of certain symptoms, etc.). An algorithm that implements classification, especially in a concrete implementation, is known as a classifier. The term classifier sometimes also refers to the mathematical function, implemented by a classification algorithm, that maps input data to a category. (https://en.wikipedia.org/wiki/Classification_in_machine_learning, Nov 28 2011)

Documentation

module Data.HInduce.Classifier.Class

confusion :: (Classifier classifier attributes label, Ord label, Fractional f) => classifier -> [(attributes, label)] -> [((label, label), f)]

Calculate the confusion matrix of a classifier. Prefer confusion' in ghci.

confusion' :: (Classifier classifier attributes label, Ord label, Show label) => classifier -> [(attributes, label)] -> Table label label Double

Like confusion, but puts it in a nice table.

absConfusion :: (Classifier classifier attributes label, Ord label) => classifier -> [(attributes, label)] -> [((label, label), Int)]

Calculate the confusion matrix of a classifier, showing numbers of occurance instead of relative frequencies. Prefer absConfusion' in ghci.

absConfusion' :: (Classifier classifier attributes label, Ord label, Show label) => classifier -> [(attributes, label)] -> Table label label Int

Like absConfusion, but puts it in a nice table.