Research On Classification Models In Machine Learning For IRIS Dataset

Clasification models in machine learning is used in various applications for prediction. It is a supervised learning model where the models can be trained with the required outputs. There are various types of classifiers such as Naïve Bayes, KNN, Decision trees and support vector machines. Neural network machine learning model is also used for classification and prediction. The IRIS dataset is most familiar and commonly used dataset for classification to predict the accuracy. The research focusses on the analysis of the KNN based classification and Naïve bayes classification algorithms for the performance analysis.