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Which of the following can be one of the steps in stacking?
1. Divide the training data into k folds
2. Train k models on each k-1 folds and get the out of fold predictions for remaining one fold
3. Divide the test data set in "k" folds and get individual fold predictions by different algorithms

Which of the following can be one of the steps in stacking?
1. Divide the training data into k folds
2. Train k models on each k-1 folds and get the out of fold predictions for remaining one fold
3. Divide the test data set in "k" folds and get individual fold predictions by different algorithms Correct Answer 1 and 2

Related Questions

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2. Start with empty ensemble
3. Return the ensemble from the nested set of ensembles that has maximum performance on the validation set
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Consider the following statements about folds: An anticline is a fold that is convex upward, and a syncline is a fold that is concave upward. An anticlinorium is a large syncline on which minor folds are superimposed, and a synclinorium is a large anticline on which minor folds are superimposed. Which of the above statements is correct?
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Suppose you are given 'n' predictions on test data by 'n' different models (M1, M2, .... Mn) respectively. Which of the following method(s) can be used to combine the predictions of these models?
Note: We are working on a regression problem
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5. Minimum and Maximum
6. Generalized mean rule
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