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Which technique is used to handle missing values in a dataset?

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Question: Which technique is used to handle missing values in a dataset?

Options:

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

Correct Answer: Imputation

Solution: 

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

Which technique is used to handle missing values in a dataset?

Practice Questions

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

Questions & Step-by-Step Solutions

Which technique is used to handle missing values in a dataset?
  • Step 1: Understand that missing values are gaps in your data where information is not available.
  • Step 2: Learn about imputation, which is a method used to fill in these gaps.
  • Step 3: Identify the type of imputation you can use, such as filling with the mean, median, or mode of the available data.
  • Step 4: Apply the chosen imputation method to replace the missing values in your dataset.
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