xenial (1) mlpack_pca.1.gz

NAME

       mlpack_pca - principal components analysis

SYNOPSIS

        mlpack_pca [-h] [-v] -i string -o string [-d int] [-s] [-V double] --version

DESCRIPTION

       This program performs principal components analysis on the given dataset. It will transform the data onto
       its principal components, optionally  performing  dimensionality  reduction  by  ignoring  the  principal
       components with the smallest eigenvalues.

REQUIRED OPTIONS

       --input_file (-i) [string]
              Input dataset to perform PCA on.

       --output_file (-o) [string]
              File to save modified dataset to.

OPTIONS

       --help (-h)
              Default help info.

       --info [string]
              Get help on a specific module or option.  Default value ''.

       --new_dimensionality (-d) [int]
              Desired dimensionality of output dataset. If 0, no dimensionality reduction is performed.  Default
              value 0.

       --scale (-s)
              If set, the data will be scaled before running PCA, such that the variance of each feature is 1.

       --var_to_retain (-V) [double]
              Amount of variance to retain; should be  between  0  and  1.  If  1,  all  variance  is  retained.
              Overrides -d. Default value 0.

       --verbose (-v)
              Display informational messages and the full list of parameters and timers at the end of execution.
              --version Display the version of mlpack.

ADDITIONAL INFORMATION

       For further information, including relevant papers, citations,  and  theory,  consult  the  documentation
       found at http://www.mlpack.org or included with your DISTRIBUTION OF MLPACK.

                                                                                                   mlpack_pca(1)