Before using the spark ML library to train the machine learning model; we are required to assemble the features into one vector. If you are given a spark dataframe DF with numerical columns ['featurel','feature2','feature3','feature4','label'] .Import all necessary libraries and write a spark code snippet to assemble features Vector for ['featurel','feature2','feature3','feature4'1

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Before using the spark ML library to train the machine learning model; we are required to assemble the features into one vector. If you are given a spark dataframe DF with
numerical columns
['featurel','feature2', 'feature3', 'feature4', 'label']
Import all necessary libraries and write a spark code snippet to assemble features
Vector for
['featurel','feature2', 'feature3', 'feature4']
Transcribed Image Text:Before using the spark ML library to train the machine learning model; we are required to assemble the features into one vector. If you are given a spark dataframe DF with numerical columns ['featurel','feature2', 'feature3', 'feature4', 'label'] Import all necessary libraries and write a spark code snippet to assemble features Vector for ['featurel','feature2', 'feature3', 'feature4']
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