Iris Classification with Lime Explainability

Using the Iris dataset and two algorithms, k-means clustering and logistic regression this project sets out to use the algorithms to classify the three species of iris contained within the dataset. The project builds a k-means cluster classifier, finding that k=3 is the optimal value for k, and a logistic regression model that provides 98% accuracy. The project also reports on the use of Lime to explain how the regression model made the classification decision.