Which of the following parameters can be tuned for finding good ensemb – McqOptions

MCQOPTIONS

1.	Which of the following parameters can be tuned for finding good ensemble model in bagging based algorithms?
A.	1
B.	2
C.	3&4
D.	1,2,3&4
Answer» E.

Discussion

No Comment Found

Related MCQs

During the last few years, many algorithms have been applied to deep
If I am using all features of my dataset and I achieve 100% accuracy on my training set, but
SVMs directly give us the posterior probabilities P(y = 1jx) and P(y = 􀀀1jx)
Which of the following is not supervised learning?
Let S1 and S2 be the set of support vectors and w1 and w2 be the learnt weight vectors for a linearly
What is the Accuracy in percentage based on following confusion matrix of three class classification.
What is true about K-Mean Clustering?
Which of the following statement is true about k-NN algorithm?
Which of the following can act as possible termination conditions in K-Means?
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 variables3. Feature normalization always helps when we use Gaussian kernel in SVM