Shiro-Raven
/ kNN.hs
Created
March 13, 2020 13:18
k-nearest neighbors using Haskell for classifying passing students
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| import Data.List | |
| data Ex = Ex Float Float String String deriving Show | |
| data NewSt = NewSt Float Float String deriving Show | |
| data Dist = Dist Float NewSt Ex deriving Show | |
| euclidean :: NewSt -> Ex -> Dist | |
| euclidean (NewSt midterm1 quiz1 name1) (Ex midterm2 quiz2 name2 label2) = (Dist (sqrt( (midterm1-midterm2)*(midterm1-midterm2) + (quiz1-quiz2)*(quiz1-quiz2))) (NewSt midterm1 quiz1 name1) (Ex midterm2 quiz2 name2 label2)) |
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| :- use_module(library(clpfd)). | |
| %10*10 test | |
| at(3, 5, c). | |
| at(5, 0, w). | |
| at(9, 6, c). | |
| %4*4 test | |
| %at(2,0,c). | |
| %at(2,1,r). |
Shiro-Raven
/ ..Image Filters Assignment
Last active
December 28, 2019 20:21
Code for the second assignment of the Computer Vision course