Challenge: Creating a Complete ML Pipeline
Now let's create a proper pipeline with the final estimator. As a result, we will get a trained prediction pipeline that can be used for predicting new instances simply by calling the .predict() method.
To train a predictor (model), you need y to be encoded. This is done separately from the pipeline we build for X. Remember that LabelEncoder is used for encoding the target.
Tarea
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You have the same penguins dataset. The task is to build a pipeline with KNeighborsClassifier as a final estimator, train it, and predict values for the X itself.
- Encode the
yvariable. - Create a pipeline containing
ct,SimpleImputer,StandardScaler, andKNeighborsClassifier. - Train the
pipeobject using the featuresXand the targety.
Solución
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