A few Python programs to showcase some fundamentals of Machine Learning.
irisDataKKN.py - I use the k-nearest neighbors (KNN) algorithm to predict the species of an iris given the sepal length, sepal width, petal length, and petal width.
irisDataLR.py - I use the logistic regression algorithm to predict the species of an iris given the sepal length, sepal width, petal length, and petal width.
modelSelection.py - I systematically determine the best model to use based on splitting the data into train and test. I apply this first to the logistic regression algorthm. I then test different values (between 1-30) to use for K in the the k-nearest neighbors (KNN) algorithm.
k-foldCrossValidation.py - I use K-fold cross validation to shuffle my training and testing sets and calculate accuracy scores for the K value in the K-nearest neighbors (KNN) algorithm.