Data Encoding Techniques in Machine Learning Quiz

Which of these is an example of a categorical data?

• Nationality

• Number of students in class

• Shoe size

• Temperature today

What are the two types of qualitative data?

• Nominal and ratio

• Ordinal and discrete

• Nominal and ordinal

• Interval and ratio

What is the purpose of encoding categorical variables in machine learning?

• To transform them into a numerical format for compatibility with algorithms

• To introduce bias in the model

• To remove all information about the categories

• To increase the dimensionality of the data

Which encoding technique is suitable for categorical features with only two distinct categories?

• One-Hot Encoding

• Label Encoding

• Ordinal Encoding

• Binary Encoding

What is the main advantage of using Target Encoding (Mean Encoding) for high cardinality categorical features?

• It discards all information about the categories

• It reduces the dimensionality of the data

• It introduces bias in the model

• It retains the information within the original feature

Which encoding technique calculates the mean of the target variable for each category and replaces the category with this average value?

• Target Encoding

• Ordinal Encoding

• Label Encoding

• One-Hot Encoding

What is the purpose of Count Encoding or Frequency Encoding?

• To discard any meaningful information or relationships

• To retain the original information about the frequency of each category

• To introduce variability into the encoded values

• To reduce dimensionality compared to one-hot encoding

Which encoding technique is based on a concept called Ordered Target Statistics and is suitable for high cardinality categorical features?

• Catboost Encoder

• Target Encoding

• Label Encoding

• One-Hot Encoding