1mlpack_linear_regression(1) General Commands Manualmlpack_linear_regression(1)
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NAME

6       mlpack_linear_regression - simple linear regression and prediction
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SYNOPSIS

9        mlpack_linear_regression [-h] [-v]
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DESCRIPTION

12       An  implementation of simple linear regression and simple ridge regres‐
13       sion using ordinary least squares. This solves the problem
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15         y = X * b + e
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17       where X (--input_file) and y  (the  last  column  of  --input_file,  or
18       --input_responses)  are  known  and  b  is the desired variable. If the
19       covariance matrix (X'X) is  not  invertible,  or  if  the  solution  is
20       overdetermined,   then   specify  a  Tikhonov  regularization  constant
21       (--lambda) greater than 0, which will regularize the covariance  matrix
22       to  make  it  invertible.  The  calculated  b  is saved to disk (--out‐
23       put_file).
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25       Optionally, the calculated value of b is used to predict the  responses
26       for another matrix X' (--test_file):
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28          y' = X' * b
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30       and  these  predicted responses, y', are saved to a file (--output_pre‐
31       dictions).  This type of regression is related to  least-angle  regres‐
32       sion, which mlpack implements with the 'lars' executable.
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OPTIONAL INPUT OPTIONS

35       --help (-h)
36              Default help info.
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38       --info [string]
39              Get  help  on  a  specific  module or option.  Default value ''.
40              --input_model_file (-m) [string] File containing existing  model
41              (parameters).  Default value ''.
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43       --lambda (-l) [double]
44              Tikhonov  regularization for ridge regression.  If 0, the method
45              reduces to linear regression.  Default value 0.
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47       --test_file (-T) [string]
48              File  containing  X'  (test  regressors).  Default   value   ''.
49              --training_file  (-t)  [string]  File  containing training set X
50              (regressors).   Default  value  ''.   --training_responses  (-r)
51              [string]  Optional  file containing y (responses). If not given,
52              the responses are assumed to be the last row of the input  file.
53              Default value ''.
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55       --verbose (-v)
56              Display  informational  messages and the full list of parameters
57              and timers at the end of execution.
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59       --version (-V)
60              Display the version of mlpack.
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OPTIONAL OUTPUT OPTIONS

63       --output_model_file (-M)  [string]  File  to  save  trained  model  to.
64       Default   value   ’'.    --output_predictions_file   (-o)  [string]  If
65       --test_file is specified, this file is where  the  predicted  responses
66       will be saved. Default value ''.
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ADDITIONAL INFORMATION

ADDITIONAL INFORMATION
70       For further information, including relevant papers, citations, and the‐
71       ory, For further information, including relevant papers, citations, and
72       theory,  consult  the  documentation  found at http://www.mlpack.org or
73       included   with   your   consult    the    documentation    found    at
74       http://www.mlpack.org  or  included  with  your DISTRIBUTION OF MLPACK.
75       DISTRIBUTION OF MLPACK.
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79                                                   mlpack_linear_regression(1)



        

    


            
        

        

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