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 problem1. Median2. Product3. Average4. Weighted sum5. Minimum and Maximum6. Generalized mean rule

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Machine learning (ML) is a branch of artificial intelligence that leverages data to improve computer performance by giving machines the ability to "learn", or improve performance — based on the data.

There are four basic approaches to machine learning: supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning.


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?<br>Note: We are working on a regression problem<br>1. Median<br>2. Product<br>3. Average<br>4. Weighted sum<br>5. Minimum and Maximum<br>6. Generalized mean rule