ylks

6 ms·

1. 1.▲
   by ylks 4y ago

   Energy is a shorthand for L2 norm (in a probabilistic sense). This similar to the definition of the energy of a signal in signal processing. 'Information content' is an alternative for 'energy' here, but it can be mistak
2. 2.▲
   by ylks 4y ago

   You nailed it.
3. 3.▲
   by ylks 4y ago

   That's precisely what the blog post deals with. In that PCA pre-processing step, nothing guarantees that principal components are better representations for your problem than original inputs; in fact PCA has nothing to do with your tar
4. 4.▲
   by ylks 4y ago

   Check out these posts: https://blog.kxy.ai/tag/feature-selection/ . This one in particular compares a few methods on 38 datasets and has some Python code: https://blog.kxy.ai/adding-feature-selectio
5. 5.▲
   by ylks 4y ago

   Feature selection ought to be model-specific. Because a feature wasn't selected by Lasso (in a linear model) does not mean it cannot be useful in a non-linear model.
6. 6.▲
   by ylks 4y ago

   Hello, I'm the author of the post. I'm slightly late to the party, but I'll try to clarify a few misunderstandings. First and foremost, the post deals with the following scenario too many data scientists find themselves in: &
7. 7.▲
   A design pattern to make ML projects lean(arxiv.org)

   3 points by ylks 5y ago|0 comments
8. 8.▲
   Show HN: KXY, an ML API to estimate the theoretical-best performance achievable(blog.kxy.ai)

   1 points by ylks 5y ago|0 comments