[Solved] The "curse of dimensionality" referes

McqMate

Q.	The "curse of dimensionality" referes
A.	all the problems that arise when working with data in the higher dimensions, that did not exist in the lower dimensions.
B.	all the problems that arise when working with data in the lower dimensions, that did not exist in the higher dimensions.
C.	all the problems that arise when working with data in the lower dimensions, that did not exist in the lower dimensions.
D.	all the problems that arise when working with data in the higher dimensions, that did not exist in the higher dimensions.
Answer» A. all the problems that arise when working with data in the higher dimensions, that did not exist in the lower dimensions.

1.7k

0

Do you find this helpful?

19

View all MCQs in

Machine Learning (ML)

Discussion

No comments yet

Related MCQs

What does dimensionality reduction reduce?
Dimensionality Reduction Algorithms are one of the possible ways to reduce the computation time required to build a model
Dimensionality reduction algorithms are one of the possible ways to reduce the computation time required to build a model.
It is not necessary to have a target variable for applying dimensionality reduction algorithms
The most popularly used dimensionality reduction algorithm is Principal Component Analysis (PCA). Which of the following is/are true about PCA? 1. PCA is an unsupervised method2. It searches for the directions that data have the largest variance3. Maximum number of principal components <= number of features4. All principal components are orthogonal to each other