In machine learning, an algorithm (or learning algorithm) is said to be unstable if a small change in training data cause the large change in the learned classifiers. True or False: Bagging of unstable classifiers is a good idea

Home / Engineering / Machine Learning (ML) / Question

Mr. Dubey • 51.43K Points
Coach

Q.) In machine learning, an algorithm (or learning algorithm) is said to be unstable if a small change in training data cause the large change in the learned classifiers. True or False: Bagging of unstable classifiers is a good idea

(A) true

(B) false

(D) ---

Correct answer : Option (A) - true

Discusssion

Related MCQs on Machine Learning (ML)

Q. NetWare IPX addressing uses a network number and a node number. Which statement is not true?

Q. The earliest calculating devices are

Q. Which steps are included in use case driven iterative development?

Q. The process of assigning the IP address for specific times to the various hosts by DHCP is called?

Q. The operation of J-K flip-flop is similar to that of the SR flip-flop except that the J-K flip-flop

Q. In real time operating system ____________

Q. An attempt to read from locked file,results in

Q. is like the building name for a website.

Q. Conflicting requirements are common in Requirement Engineering, with each client proposing his or her version is the right one.

Q. Transformation of a system from one representational form to another is known as