K Nearest Neighbors algorithm

python_version = 3.6 dependencies = math, heapq, unittest

Both KNN_2D.py and AnySizeKNN.py instanciate a class for their respective solvers with 3 arguments: - reference point argument (ref_point) that defaults to (0,0). With which all euclidan distances will be calculated from. - K argument (k) that defaults to 2, that defines the amount of nearest neighbors you'd like to return. - data set argument (data_set), which is all the data points to be analyzed. Note: for KNN_2D.py all datapoints must be of 2 dimensions (example: (3,2)), for AnySizeKNN.py the data points can be any size you want, from 1 to infinity (I wouldn't recomend infinity though, lol)

How to Run: 1)Open command line. 2)Run command for script you'd like to run (I recommend the GUI) GUI: $python run.py 2D KNN: $python KNN_2D.py Any Size Vector KNN: $python AnySizeVectorKNN.py tests: $python test_KNN.py