All of the following are disadvantages/limitations of the SVM technique EXCEPT
A) model building involves complex and time-demanding calculations.
B) selection of the kernel type and kernel function parameters is difficult.
C) they have high algorithmic complexity and extensive memory requirements for complex tasks.
D) their accuracy is poor in many domains compared to neural networks.

Question

Quizplus · Accepted Answer

The statement that "their accuracy is poor in many domains compared to neural networks" is not a disadvantage/limitation of the SVM technique. It is actually a debatable statement and depends on the specific problem and data. The other options listed are recognized as disadvantages/limitations of SVM technique.

All of the Following Are Disadvantages/limitations of the SVM Technique