Consider the following statements:
A. C-fuzzy means clustering is a supervised method of learning.
B. PCA is used for dimension reduction.
C. Apriori is not a supervised technique.
D. When a machine-learning model becomes so specially tuned to its exact input data that it fails to generalise to other similar data, it is called underfitting.
Choose the correct answer from the options given below:
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Correct answer: B. B and C
Explanation
Fuzzy C-means is unsupervised clustering (A false). PCA reduces dimensions (B true). Apriori is unsupervised association-rule mining (C true). D describes overfitting, not underfitting.More Artificial Intelligence (AI) questions
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