Adaptation of autoencoder for sparsity reduction from clinical notes representation learning

HIGHLIGHTS

• who: Thanh-Dung Le and colleagues from the AData Sparsity Challenges In numerical analysis, a sparse matrix or sparse array is a matrix in which most elements are zero [17]. The number of zero-valued elements divided by the total number of elements (e_g, m u00d7 n for a m u00d7 n matrix) is called the matrix sparsity (equal to , minus the density of the matrix). Using these definitions, a matrix will be sparse when its sparsity is more significant than, .5. In our case, after the research protocol was approved by the research ethics board from . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.