Data Preprocessing Quiz

What is the primary goal of data preprocessing?

• To remove all data points

• To enhance data quality for better analysis

• To increase data redundancy

• To randomly select features

Which technique is commonly used to handle missing data?

• Deleting the entire dataset

• Filling missing values with the mean or median

• Ignoring the issue

• Adding random values

What is feature selection in machine learning?

• Removing all attributes from the dataset

• Choosing relevant variables to improve model performance

• Duplicating existing features

• Adding random variables

What is the purpose of data cleaning?

• To introduce new errors

• To standardize and correct inconsistencies in the data

• To remove all categorical variables

• To duplicate the dataset for backup

Which of the following is NOT a step in data preprocessing?

• Data integration

• Data redundancy

• Data transformation

• Data cleaning

What is the main purpose of data integration?

• Combining data from multiple sources into a unified format

• Removing duplicate data

• Randomly splitting data

• Encrypting data for security

What is feature engineering?

• The process of creating new meaningful features from raw data

• The removal of all missing values

• The deletion of unnecessary columns

• The process of merging datasets

Why is data discretization used?

• To transform continuous data into discrete categories

• To remove all numerical values

• To increase data storage

• To improve missing value handling

What is a data warehouse?

• A storage facility for unstructured data only

• A central repository for structured data used for analysis

• A tool for data visualization

• A machine learning model

What is one challenge of data integration?

• Data inconsistency across multiple sources

• Data preprocessing speed

• Lack of storage space

• Data encryption