ML Introduction with scikit-learn
In this challenge, you will build and evaluate a model using both train-test evaluation and cross-validation.
The data is an already preprocessed Penguins dataset.
Some functions you will use:
Build a 4-nearest neighbors classifier and evaluate its performance using the cross-validation score first, then split the data into train-test sets, train the model using the training set, and evaluate it using the test set.
- Initialize a
KNeighborsClassifierwith 4 neighbors.
- Calculate the cross-validation scores of this model with the number of folds set to 3.
Note: you can pass an untrained model to a
- Use a suitable function to split
- Train the model using the training set.
- Evaluate the model using the test set.
Everything was clear?
Section 4. Chapter 5