Data Preprocessing Quiz

Which of the following is NOT a method for handling missing values in a dataset?

• Filling with mean

• Filling with median

• Filling with random numbers

• Dropping the missing rows

Which preprocessing technique ensures that all features have a mean of 0 and a standard deviation of 1?

• Min-Max Scaling

• Robust Scaling

• Standardization

• Normalization

One-Hot Encoding is preferred over Label Encoding when:

• The categorical variable is ordinal.

• The categorical variable is nominal.

• The categorical variable has missing values.

• The variable is numerical.

What is the main advantage of using a data preprocessing pipeline in Scikit-learn?

• It reduces the dataset size.

• It automates preprocessing steps and ensures consistency.

• It automatically tunes model hyperparameters.

• It generates more training data.

Which of the following is most robust to outliers?

• Min-Max Scaler

• Standard Scaler

• Robust Scaler

• Normalizer

Which function in Python is commonly used to check for missing values in a dataset?

• pd.isnull()

• pd.fillna()

• pd.dropna()

• pd.groupby()

What is the default strategy of SimpleImputer when used for numerical data?

• Median

• Mean

• Most Frequent

• Zero

In text preprocessing, which of the following steps is typically performed first?

• Stopword removal

• Lowercasing text

• Lemmatization

• Stemming

If you have a numerical feature with extreme outliers, which scaling method is most appropriate?

• Min-Max Scaler

• Standard Scaler

• Robust Scaler

• Normalizer

In correlation analysis, a correlation coefficient close to zero indicates:

• Strong positive correlation

• Strong negative correlation

• No linear relationship

• Perfect correlation