Bissoy.com
Doctors Medicines MCQs Q&A

Related Questions

User level threads are threads that are visible to the programmer and are unknown to the kernel. The operating system kernel supports and manages kernel level threads. Three different types of models relate user and kernel level threads. Which of the following statements is/are true ? (a) (i) The Many - to - one model maps many user threads to one kernel thread (ii) The one - to - one model maps one user thread to one kernel thread (iii) The many - to - many model maps many user threads to smaller or equal kernel threads (b) (i) Many - to - one model maps many kernel threads to one user thread (ii) One - to - one model maps one kernel thread to one user thread (iii) Many - to- many model maps many kernel threads to smaller or equal user threads
To build a modularized kernel, the kernel-headers and kernel-source packages must first be installed. Where will you find the kernel-headers and kernel-source?
Given below are six sentences 4 of which are jumbled. The first and the last sentence are given. Pick the option that gives the logically correct order of the four sentences. S1: The salt seller came to understand the trick and decided to teach the donkey a lesson. A: But the dampened cotton became very heavy to carry and the donkey suffered. B: It learnt a lesson. C: Again it played the same trick hoping that the cotton bag would become lighter. D: The next day he loaded a cotton bag on the donkey. S6: It didn’t play the trick anymore after that day, and the salt seller was happy.
In the context of machine learning, what is the purpose of the "kernel trick" in support vector machines (SVMs)?
Which of the following statements is not true about kernel trick?
The kernel trick
After you have compiled your kernel, what do you have to edit to boot your new kernel image?
The Gaussian kernel is also called the RBF kernel, for Radial Basis Functions.
We usually use feature normalization before using the Gaussian kernel in SVM. What is true about feature normalization?
1. We do feature normalization so that new feature will dominate other
2. Some times, feature normalization is not feasible in case of categorical variables
3. Feature normalization always helps when we use Gaussian kernel in SVM
Give the correct Answer for following statements. 1. It is important to perform feature normalization before using the Gaussian kernel. 2. The maximum value of the Gaussian kernel is 1.