Iris Classifier
This model is trained on the Iris dataset to classify iris flowers into three species: setosa, versicolor, and virginica. It uses a Decision Tree algorithm for classification.
Model Architecture
The model is a decision tree classifier, chosen for its simplicity and interpretability. The decision tree learns to split the data based on feature values to classify the iris species.
Training Process
The model was trained on the Iris dataset, which contains 150 samples with 4 features each: sepal length, sepal width, petal length, and petal width. The dataset is split into training and testing sets, and the model is trained using the training set. The accuracy of the model is evaluated on the testing set.
Performance
The model achieves high accuracy on the Iris dataset, demonstrating its effectiveness in classifying the iris specie22h.p]
