M

Mr. Dubey • 53.53K Points
Coach

Q. . . . . . . . . performs a PCA with non-linearly separable data sets.

  • (A) SparsePCA
  • (B) KernelPCA
  • (C) SVD
  • (D) None of the Mentioned

No solution found for this question.
Add Solution and get +2 points.

You must be Logged in to update hint/solution

Discusssion

Login to discuss.

Be the first to start discuss.

Related MCQs on Machine Learning

Q. Which syntax is used to describe elements in CSS?

Q. According to . . . . . . . . , it's a key success factor for the survival and evolution of all species.

Q. If two variables are correlated, is it necessary that they have a linear relationship?

Q. Which of the following assumptions do we make while deriving linear regression parameters? 1. The true relationship between dependent y and predictor x is linear 2. The model errors are statistically independent 3. The errors are normally distributed with a 0 mean and constant standard deviation 4. The predictor x is non-stochastic and is measured error-free

Q. What is the precision value for following confusion matrix of binary classification?

Q. What is the Accuracy in percentage based on following confusion matrix of three class classification. Confusion Matrix C= [14 0 0] [ 1 15 0] [ 0 0 6]

Q. Below are the two ensemble models: 1. E1(M1, M2, M3) and 2. E2(M4, M5, M6) Above, Mx is the individual base models. Which of the following are more likely to choose if following conditions for E1 and E2 are given? E1: Individual Models accuracies are high but models are of the same type or in another term less diverse E2: Individual Models accuracies are high but they are of different types in another term high diverse in nature

Q. Which is the object on which the event occured or with which the event is associated?

Q. What is/are true about ridge regression? 1. When lambda is 0, model works like linear regression model 2. When lambda is 0, model doesn't work like linear regression model 3. When lambda goes to infinity, we get very, very small coefficients approaching 04. When lambda goes to infinity, we get very, very large coefficients approaching infinity.

Q. What does /[^(]* regular expression indicate ?

Learn All Machine Learning MCQs


Question analytics