What is the process of converting categorical variables into numerical values for machine learning called?

Feature Extraction
Data Encoding
Data Standardization
Label Encoding

The correct answer is: B. Data Encoding

Data encoding is the process of converting categorical variables into numerical values for machine learning. This is done by assigning a unique number to each category. For example, if you have a categorical variable called “gender” with the categories “male” and “female”, you could encode it as follows:

  • Male = 0
  • Female = 1

Once the data has been encoded, it can be used by machine learning algorithms.

The other options are incorrect for the following reasons:

  • Feature extraction is the process of identifying and selecting the most important features from a dataset.
  • Data standardization is the process of normalizing the data so that it has a mean of 0 and a standard deviation of 1.
  • Label encoding is the process of assigning unique numbers to each class in a classification problem.