Mushrooms: a matter of life or death

Let's conclude the course by revisiting the mushroom edibility problem. You'll try the stacking classifier to see if the score can be improved. As stacking uses a meta-estimator (second layer classifier) which attempts to correct predictions from the first layer, some of the misclassified instances could be corrected. This is a very important problem, as the edibility of a mushroom is a matter of life or death.

The dataset has been loaded and split into train and test sets. Do you think stacking can help to predict the edibility of a mushroom with greater confidence?

Instantiate the first-layer estimators: a 5-nearest neighbors using the ball tree algorithm, a decision tree classifier with parameters min_samples_leaf = 5 and min_samples_split = 15, and a Gaussian Naive Bayes classifier.
Build and fit a stacking classifier, using the parameters classifiers - a list containing the first-layer classifiers - and meta_classifier - the default logistic regression.

Exercise

Mushrooms: a matter of life or death

Instructions