• Corpus ID: 2940406

Sparse mean localization by information theory

@article{Diaz2017SparseML,
  title={Sparse mean localization by information theory},
  author={Emiliano Diaz},
  journal={ArXiv},
  year={2017},
  volume={abs/1704.00575}
}
Sparse feature selection is necessary when we fit statistical models, we have access to a large group of features, don't know which are relevant, but assume that most are not. Alternatively, when the number of features is larger than the available data the model becomes over parametrized and the sparse feature selection task involves selecting the most informative variables for the model. When the model is a simple location model and the number of relevant features does not grow with the total… 

References

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# set . seed (4) 333 data . arr ← sim . data (n , noise . level , dim . data , dimnames . data )
  • # set . seed (4) 333 data . arr ← sim . data (n , noise . level , dim . data , dimnames . data )
1 ,1] ← res . mean . n2 $ info $ sd . gen . capacity [ choose . sparsity ,] 193 sd . gen . capacity [i
  • 1 ,1] ← res . mean . n2 $ info $ sd . gen . capacity [ choose . sparsity ,] 193 sd . gen . capacity [i
1 ,2] ← res . mean . n1 $ info $ sd . gen . capacity [ choose . sparsity ,] 200 sd . gen . capacity [i
  • 1 ,2] ← res . mean . n1 $ info $ sd . gen . capacity [ choose . sparsity ,] 200 sd . gen . capacity [i
1]) 222 plot ( ds , gen . capacity [ ,1 ,1 ,1] , ylim = c (0 , max . gen ) , col = " blue " , pch =1 , type = " b " , xlab = " Dimension d " , ylab = " generalization capacity
  • 1]) 222 plot ( ds , gen . capacity [ ,1 ,1 ,1] , ylim = c (0 , max . gen ) , col = " blue " , pch =1 , type = " b " , xlab = " Dimension d " , ylab = " generalization capacity
210 finish ← finish [2: length ( finish ) ] 211 plot ( ds , finish )
  • 210 finish ← finish [2: length ( finish ) ] 211 plot ( ds , finish )
2]) 252 plot ( ds , gen . capacity [ ,1 ,1 ,2] , ylim = c (0 , max . gen ) , col = " blue " , pch =1 , type = " b " , xlab = " Dimension d " , ylab = " generalization capacity
  • 2]) 252 plot ( ds , gen . capacity [ ,1 ,1 ,2] , ylim = c (0 , max . gen ) , col = " blue " , pch =1 , type = " b " , xlab = " Dimension d " , ylab = " generalization capacity
319 for ( i in 1: length ( ds )
  • 319 for ( i in 1: length ( ds )
353 gen . capacity [i ,2] ← res . imp . smpl . mean . n1 $ info $ gen
  • 353 gen . capacity [i ,2] ← res . imp . smpl . mean . n1 $ info $ gen
367 finish ← finish [2: length ( finish ) ] 368 plot ( ds , finish
  • 367 finish ← finish [2: length ( finish ) ] 368 plot ( ds , finish
A.2 Script 81
  • A.2 Script 81
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