The number one reason why orthogonality is essential in data science: uncorrelating features.
However, the features we are given are rarely such. There are ways to fix this, and the Gram-Schmidt process is one of them.
Here is how it works.
The number one reason why orthogonality is essential in data science: uncorrelating features.
However, the features we are given are rarely such. There are ways to fix this, and the Gram-Schmidt process is one of them.
Here is how it works.