Description: K-nearest neighbours classifier is a method that looks at the observation that are nearest to one it's trying to predict and classifies the point of interest based on the majority of those around it. This particular code contains two data sets that allow user to see how acurate can that method be. First user has to choose one of those sets (iris or cancer, links to their descriptions are down below), then has to determine what calculating method they want to use (euclidean or maanhatan) and finally decide how many neighbours are to be considered in classifying. Software uses training data sets and compare k nearest neighbours to test data sets. Then finally provides us with the information about its accuracy. Also, it creates a text file where result is stored.
In order to run an app, go to project folder and find the "start.bat" file. Then simply run it.
Sources:
https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm
https://archive.ics.uci.edu/ml/datasets/iris
https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data