SYNOPSIS

linear_regression [-h] [-v] [-i string] [-r string] [-l double] [-m string] [-o string] [-p string] [-t string] -V

DESCRIPTION

An implementation of simple linear regression and simple ridge regression using ordinary least squares. This solves the problem

  y = X * b + e

where X (--input_file) and y (the last column of --input_file, or --input_responses) are known and b is the desired variable. If the covariance matrix (X'X) is not invertible, or if the solution is overdetermined, then specify a Tikhonov regularization constant (--lambda) greater than 0, which will regularize the covariance matrix to make it invertible. The calculated b is saved to disk (--output_file).

Optionally, the calculated value of b is used to predict the responses for another matrix X' (--test_file):

   y' = X' * b

and these predicted responses, y', are saved to a file (--output_predictions). This type of regression is related to least-angle regression, which mlpack implements with the 'lars' executable.

REQUIRED OPTIONS

OPTIONS

--help (-h)

Default help info.

--info [string]

Get help on a specific module or option. Default value ''.

--input_file (-i) [string]

File containing X (regressors). Default value ''.

--input_responses (-r) [string]

Optional file containing y (responses). If not given, the responses are assumed to be the last row of the input file. Default value ''.

--lambda (-l) [double]

Tikhonov regularization for ridge regression. If 0, the method reduces to linear regression. Default value 0.

--model_file (-m) [string]

File containing existing model (parameters). Default value ''.

--output_file (-o) [string]

File where parameters (b) will be saved. Default value 'parameters.csv'.

--output_predictions (-p) [string]

If --test_file is specified, this file is where the predicted responses will be saved. Default value 'predictions.csv'.

--test_file (-t) [string]

File containing X' (test regressors). Default value ''.

--verbose (-v)

Display informational messages and the full list of parameters and timers at the end of execution.

--version (-V)

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.