The correct answer is B. E2.
Ensemble models are a type of machine learning model that combine the predictions of multiple models to produce a more accurate prediction. The idea is that if each model makes a different mistake, then the ensemble model will be less likely to make that mistake.
In the case of E1, the individual models are all of the same type, so they are likely to make the same mistakes. This means that the ensemble model is not likely to be more accurate than any of the individual models.
In the case of E2, the individual models are of different types, so they are less likely to make the same mistakes. This means that the ensemble model is more likely to be more accurate than any of the individual models.
Therefore, E2 is more likely to be chosen than E1.
Here is a more detailed explanation of each option:
A. E1: Individual Models accuracies are high but models are of the same type or in another term less diverse.
In this case, the individual models are all of the same type, so they are likely to make the same mistakes. This means that the ensemble model is not likely to be more accurate than any of the individual models.
B. E2: Individual Models accuracies are high but they are of different types in another term high diverse in nature.
In this case, the individual models are of different types, so they are less likely to make the same mistakes. This means that the ensemble model is more likely to be more accurate than any of the individual models.
C. any of e1 and e2
This option is not correct because E1 is not likely to be more accurate than any of the individual models, while E2 is more likely to be more accurate than any of the individual models.
D. none of these
This option is not correct because E2 is more likely to be more accurate than any of the individual models.