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Which technique can be used to handle missing data in a dataset?

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Question: Which technique can be used to handle missing data in a dataset?

Options:

  1. Feature scaling
  2. Imputation
  3. Normalization
  4. Regularization

Correct Answer: Imputation

Solution: 

Imputation is a technique used to fill in missing values in a dataset.

Which technique can be used to handle missing data in a dataset?

Practice Questions

Q1
Which technique can be used to handle missing data in a dataset?
  1. Feature scaling
  2. Imputation
  3. Normalization
  4. Regularization

Questions & Step-by-Step Solutions

Which technique can be used to handle missing data in a dataset?
  • Step 1: Identify the missing data in your dataset.
  • Step 2: Choose a method to fill in the missing values, such as using the average, median, or mode of the existing data.
  • Step 3: Apply the chosen method to replace the missing values with the calculated values.
  • Step 4: Verify that the missing values have been filled correctly.
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