K-nearest neighbors for mushrooms
The Gaussian Naive Bayes classifier did a really good job for being an initial model. Let's now build a new model to compare it against the Naive Bayes.
In this case, the algorithm to use is a 5-nearest neighbors classifier. As the dummy features create a high-dimensional dataset, use the Ball Tree algorithm to make the model faster. Let's see how this model performs!
Latihan ini adalah bagian dari kursus
Ensemble Methods in Python
Petunjuk latihan
- Build a
KNeighborsClassifierwith5neighbors andalgorithm = 'ball_tree'(to expedite the processing). - Fit the model to the training data.
- Evaluate the performance on the test set using the accuracy score.
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
# Instantiate a 5-nearest neighbors classifier with 'ball_tree' algorithm
clf_knn = ____(____, ____)
# Fit the model to the training set
____
# Calculate the predictions on the test set
pred = ____
# Evaluate the performance using the accuracy score
print("Accuracy: {:0.4f}".format(accuracy_score(y_test, pred)))