
Ultimate access to all questions.
In the context of feature selection using Spark ML, explain the process of selecting the most relevant features for a machine learning model. Provide a code snippet demonstrating the use of Spark ML's feature selection techniques, such as ChiSqSelector or RFE (Recursive Feature Elimination), and explain the key considerations to keep in mind during this process.
A
Use the ChiSqSelector class from the pyspark.ml.feature module to select the top k features with the highest chi-squared statistics for categorical features.
B
Use the RFE class from the pyspark.ml.feature module to perform recursive feature elimination based on the importance of features learned by a machine learning model.
C
Use the VectorSlicer class from the pyspark.ml.feature module to select a subset of features from a vector column.
D
Use the MinMaxScaler class from the pyspark.ml.feature module to scale the features to a specific range, without performing feature selection.