What are the Disadvantages of Dimensionality Reduction?

Data Science, AI and ML
#1

Some of the disadvantages of Dimensionality reduction are as follows:

1. While doing dimensionality reduction, we lost some of the information, which can possibly affect the performance of subsequent training algorithms.

2. It can be computationally intensive.

3. Transformed features are often hard to interpret.

4. It makes the independent variables less interpretable.