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How can we assign the weights to output of different models in an ensemble?
1. Use an algorithm to return the optimal weights
2. Choose the weights using cross validation
3. Give high weights to more accurate models

How can we assign the weights to output of different models in an ensemble?
1. Use an algorithm to return the optimal weights
2. Choose the weights using cross validation
3. Give high weights to more accurate models Correct Answer all of above

Related Questions

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
Regarding bias and variance, which of the following statements are true? (Here 'high' and 'low' are relative to the ideal model.
i. Models which overfit are more likely to have high bias
ii. Models which overfit are more likely to have low bias
iii. Models which overfit are more likely to have high variance
iv. Models which overfit are more likely to have low variance
Regarding bias and variance, which of the following statements are true? (Here 'high' and 'low' are relative to the ideal model. (i) Models which overfit are more likely to have high bias (ii) Models which overfit are more likely to have low bias (iii) Models which overfit are more likely to have high variance (iv) Models which overfit are more likely to have low variance
Match List I with List II List I List II (A) Greedy Best-First Search (I) Space complexity is O(d) where d = depth of the deepest optimal solution (B) A* (II) Incomplete even if the search space is finite. (C) Recursive Best-First Search (III) Optimal if optimal solution is reachable: otherwise, returns the best reachable optimal solution. (D) SMA* (IV) Computation and space complexity is too high.   Choose the correct answer from the options given below:
Four friends A, B, C and D need to cross a bridge. A maximum two persons can cross it at a time. It is night and they just have one lamp. Persons that cross the bridge must carry the lamp to find the way. A pair must walk together at the speed of slower person. After crossing the bridge, the person having faster speed in the pair will return with the lamp each time to accompany another person in the group. Finally, the lamp has to be returned at the original place and the person who returns the lamp has to cross the bridge again without lamp. To cross the bridge, the time taken by them is as follows: A :1 minute, B : 2 minutes, C : 7 minutes and D : 10 minutes. What is the total minimum time required by all the friends to cross the bridge?
Two stock options are available for buying. Each offers a variable rate of return of profit over a period of 10 years. For first 4 years one has an incremental rate of return which increases by 2% per year starting from 3% of the investment and stays constant at 8% for the rest of the period. The second one has a constant annual rate of return throughout and give 10% more return after 10 years. What is the annual rate of return on second option?
Which of the following statements are true? (A) Minimax search is breadth-first: it processes all the nodes at a level before moving to a node in next level. (B) The effectiveness of the alpha-beta pruning is highly dependent on the order in which the states are examined. (C) The alpha-beta search algorithm computes the same optimal moves as minimax algorithm. (D) Optimal play in games of imperfact information does not require reasoning about the current and future belief states of each player. Choose the correct answer from the options given below:
Which of the following can be true for selecting base learners for an ensemble?
1. Different learners can come from same algorithm with different hyper parameters
2. Different learners can come from different algorithms
3. Different learners can come from different training spaces
Which of the following is true about weighted majority votes?
1. We want to give higher weights to better performing models
2. Inferior models can overrule the best model if collective weighted votes for inferior models is higher than best model
3. Voting is special case of weighted voting
Which of the following statements are true? (A) An algorithm may produce no output (B) An algorithm expressed in a programming language is called a computer program. (C) An algorithm is expressed in a graphical form known as a flowchart (D) An algorithm can have an infinite sequence of instructions. Choose the correct answer from the options given below: