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Answer: Train the model after selecting and preprocessing features.
To train a machine learning model using features from a feature store table, you would first select the relevant features based on the problem requirements. Then, you would preprocess the features, which may include scaling, encoding, or transformation. The code snippet would include reading the features from the feature store table, applying the preprocessing steps, and training the model.
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Discuss the process of training a machine learning model using features from a feature store table in Databricks. Include the necessary code snippets and considerations for feature selection and preprocessing.
A
Train the model directly using all features without preprocessing.
B
Train the model after selecting features but without preprocessing.
C
Train the model after selecting and preprocessing features.
D
Train the model directly using all features with preprocessing.