Q25
In data science, what is the primary goal of dimensionality reduction techniques like Principal Component Analysis (PCA)?
A.
To reduce the number of features while preserving important information
AnswerB.
To add more features to the dataset
C.
To normalize data
D.
To visualize data
Answer: Option A
Solution
Answer: Option A
No explanation is given for this question Let's Discuss on Board