Data Reduction Techniques Quiz

Play an AI-generated podcast conversation about this lesson

Which of the following is the main purpose of data normalization?

To reduce the range of values in each numerically valued variable to a standard range (correct)

To convert numeric variables into discrete representations

To derive new and more informative variables from the existing ones

To remove erroneous values from the data

What is the primary purpose of discretizing or aggregating data?

To convert numeric variables into discrete representations or reduce the number of values in categorical variables (correct)

To normalize the data to a standard range

To remove erroneous values from the data

To construct new attributes by deriving new variables from the existing ones

Which of the following is a key step in the data cleaning process?

Constructing new attributes by deriving new variables from the existing ones

Normalizing the data to a standard range

Converting numeric variables into discrete representations using range- or frequency-based binning techniques

Identifying and eliminating erroneous values in the data, such as odd values, inconsistent class labels, or odd distributions (correct)

What is the primary purpose of constructing new attributes by deriving new variables from the existing ones?

To create new and more informative variables that can potentially improve the performance of data mining models Signup and view all the answers

Which of the following is a common technique used for data normalization?

Reducing the range of values in each numerically valued variable to a standard range, such as 0 to 1 or -1 to +1 Signup and view all the answers

Which of the following is a key data transformation technique used to reduce the number of values in categorical variables?

Applying proper concept hierarchies to aggregate the values in categorical variables Signup and view all the answers

What is the primary purpose of log transformations in data preprocessing?

To construct new attributes by deriving new variables from the existing ones using a wide range of mathematical functions, including log transformations Signup and view all the answers

Which of the following is a common method for discretizing numeric variables?

Applying range-based or frequency-based binning techniques to convert numeric variables into discrete representations Signup and view all the answers

What is the primary purpose of principal component analysis (PCA) in data preprocessing?

To reduce the dimensionality of the dataset by transforming the original variables into a smaller set of uncorrelated variables (principal components) that capture the majority of the variance in the data Signup and view all the answers

Which of the following is a key step in the random sampling process for data preprocessing?

Selecting a subset of the data that is representative of the overall population, ensuring that the sample is random and unbiased Signup and view all the answers