I tried to use Auto Encoder and PCA to do Dimensionality Reduction.
The dataset is from House Prices: Advanced Regression Techniques.
I transformed the data from 79D to 30D, and then reconstruct the data to 70D.
Here’s the result:
As you can see, PCA even did a better job.
And now I come to a conclusion that Auto Encoder is good at seeking different patterns and when fitting a single pattern PCA is a better choice.