Challenge: Putting It All Together
In this challenge, you will apply everything you learned throughout the course from data preprocessing to training and evaluating the model.
Завдання
Swipe to start coding
- Encode the target.
- Split the data so that 33% is used for the test set and the remainder for the training set.
- Make a
ColumnTransformerto encode only the'island'and'sex'columns. Make sure the others columns remain untouched. Use a proper encoder for nominal data. - Fill the gaps in a
param_gridto try the following values for the number of neighbors:[1, 3, 5, 7, 9, 12, 15, 20, 25]. - Create a
GridSearchCVobject with theKNeighborsClassifieras a model. - Construct a pipeline that begins with
ctas the first step, followed by imputation using the most frequent value, standardization, and concludes withGridSearchCVas the final estimator. - Train the model using a pipeline on the training set.
- Evaluate the model on the test set. (Print its score)
- Get a predicted target for
X_test. - Print the best estimator found by
grid_search.
Рішення
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Секція 4. Розділ 10
single
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Completion rate improved to 3.13Challenge: Putting It All Together
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In this challenge, you will apply everything you learned throughout the course from data preprocessing to training and evaluating the model.
Завдання
Swipe to start coding
- Encode the target.
- Split the data so that 33% is used for the test set and the remainder for the training set.
- Make a
ColumnTransformerto encode only the'island'and'sex'columns. Make sure the others columns remain untouched. Use a proper encoder for nominal data. - Fill the gaps in a
param_gridto try the following values for the number of neighbors:[1, 3, 5, 7, 9, 12, 15, 20, 25]. - Create a
GridSearchCVobject with theKNeighborsClassifieras a model. - Construct a pipeline that begins with
ctas the first step, followed by imputation using the most frequent value, standardization, and concludes withGridSearchCVas the final estimator. - Train the model using a pipeline on the training set.
- Evaluate the model on the test set. (Print its score)
- Get a predicted target for
X_test. - Print the best estimator found by
grid_search.
Рішення
Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантівВсе було зрозуміло?
Дякуємо за ваш відгук!
Awesome!
Completion rate improved to 3.13Секція 4. Розділ 10
single
