Q. ________is much more difficult because it's necessary to determine a supervised strategy to train a model for each feature and, finally, to predict their value

  • (A) Removing the whole line
  • (B) Creating sub-model to predict those features
  • (C) Using an automatic strategy to input them according to the other known values
  • (D) All above
πŸ’¬ Discuss
βœ… Correct Answer: (B) Creating sub-model to predict those features

Q. How it's possible to use a different placeholder through the parameter_______.

  • (A) regression
  • (B) classification
  • (C) random_state
  • (D) missing_values
πŸ’¬ Discuss
βœ… Correct Answer: (D) missing_values

Q. If you need a more powerful scaling feature, with a superior control on outliers and the possibility to select a quantile range, there's also the class________.

  • (A) RobustScaler
  • (B) DictVectorizer
  • (C) LabelBinarizer
  • (D) FeatureHasher
πŸ’¬ Discuss
βœ… Correct Answer: (A) RobustScaler

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