ML-Data Types

Categorical data can be divided into which two subtypes?

• Discrete and Continuous

• Ordinal and Nominal

• Structured and Unstructured

• Labeled and Unlabeled

Which of the following is an example of ordinal data?

• Blood group (A, B, AB, O)

• Phone number

• Rating scale (Good, Better, Best)

• Name of a person

Which of the following is NOT a method for handling missing values?

• Deletion

• Imputation

• Mean substitution

• Encryption

What is a common way to fill missing numerical values?

• Replacing with mode

• Replacing with mean or median

• Dropping the column

• Using one-hot encoding

What is the purpose of encoding in machine learning?

• To replace missing values

• To convert categorical data into numerical form

• To delete unwanted columns

• To split data into training and testing sets

Which encoding technique creates separate binary columns for each category?

• Label Encoding

• One-Hot Encoding

• Mean Encoding

• Frequency Encoding

What is the major drawback of one-hot encoding?

• It cannot handle missing values

• It changes the data type to categorical

• It does not work with ordinal data

• It increases dimensionality when categories are large

Label encoding assigns ________ to categorical values.

• Unique numerical values

• Probability values

• Random text labels

• A binary representation

Binary encoding is a combination of which two encoding techniques?

• Label encoding and binary representation

• Ordinal encoding and mean encoding

• One-hot encoding and label encoding

• One-hot encoding and mode imputation

A dataset contains movie ratings (Excellent, Good, Average, Bad). Which encoding method is best?

• One-hot encoding

• Binary encoding

• Mode imputation

• Label encoding