Project of Machine Learning
Create the best classification model that can separate the types of IRIS flowers. The stages include: importing all library needs, loading datasets and displaying data contents, preprocessing data, data visualization, breaking data for testing and training, testing model results, training machine learning models, evaluating performance (confusion matrix), visualizing results and performance, and finally the performance evaluation (accuracy and F1 score). For the dataset taken from IRIS SKLEARN and the best accuracy was with 0.9333333333333333 with k = 2.