Supervised Learning

In '4 Introduction to Scikit-Learn' the iris dataset was introduced. Import the dataset into this notebook and perform a train-test-split on it:

Now, train a Gaussian naive Bayes classifier on the training data (i.e. X_train and y_train).

Note:
We haven't talked about this classifier, but about the API Scikit-Learn uses. That is sufficient to complete this task. Gaussian naive Bayes is a proper model here, because it is fast and has no hyperparameters to choose. Gaussian naive Bayes is often a good model to use as a baseline classification.

Predict the labels of the samples in the test set and use the accuracy_score method to evaluate your results.