APPLICATION OF SUPERVISED LEARNING
CLASSIFICATION IN MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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I have 4 variables in the dataset such as-A, B, C & D. I have performed the following actions:Step 1:Using the above variables, I have created two more variables, namely E = A + 3 * B and F = B + 5 * C + D.Step 2:Then using only the variables E and F I have built a Random Forest model.Could the steps performed above represent a dimensionality reduction method?
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TRUE
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FALSE
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Either A or B
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None of the above
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Explanation:
Detailed explanation-1: -pca = PCA(n components = number of Principal Components )
Detailed explanation-2: -pca = PCA(n components=?) In other words, when we apply PCA to the original dataset with p number of variables to get a transformed dataset with k number of variables (principal components), n components is equal to k, where the value of k is much less than the value of p.
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