Iris_Classifier

The Iris Classifier project uses a Naive Bayes algorithm to classify iris species. The dataset includes features such as sepal length, sepal width, petal length, and petal width, with the target variable being the species. The data is split into training and testing sets, and the Gaussian Naive Bayes classifier is trained on the training set. The model achieved an accuracy of 1.0 on the test set.
Accuracy: 1.0
Precision, Recall, F1-Score: 1.0 for all classes

The classification report and confusion matrix confirm the model's perfect performance in predicting all iris species.