[amp_mcq option1=”Feature Extraction” option2=”Data Encoding” option3=”Data Standardization” option4=”Label Encoding” correct=”option2″]
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.