This is the command mlpack_pca that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
PROGRAM:
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)
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