This repository has been created as part of my Data Science and Business Analytics Internship (GRIP) at the Sparks Foundation. The current task is to predict the species of iris flowers based on different features such as Sepal Length, Sepal Width, Petal Length and Petal Width. The dataset contains 150 observations and 3 different classes: Iris-setosa, Iris-versicolor and Iris-virginica. The dataset has also been attached.
Decision Tree has been employed for this classification problem. Since this is a multi-class classification, the overall accuracy has been reported while the values of precision, recall and f1-score have been reporeted for each class.
In addition, the ROC curve and AUC scores have been generated using the One-vs-Rest Classifer approach.