NORM_MAP(1)

NAME
norm_map - Normalization Program for mapping data

SYNOPSIS
Calculates normalization parameters for input/output mapping data bases.

norm_map [ -pathdata directory ] -finput file
-fdescribe file [ -normalization n ] [ -fparam file ]
[ -debug n ] [ -verbose n ]

EXAMPLE
norm_map -pathdata $LNKHOME/data/class \
-finput gauss_map.train \
-fdescribe gauss_map.train.defaults -normalization 1 \
-fparam gauss_map.norm.simple

DESCRIPTION
LNKmap input/output mapping and clustering programs normalize input data using parameters calculated by the program norm_map. The normalization parameters for a data base are calculated based on the training data file and applied to all input patterns, training or testing, when they are read by a LNKmap program. Three types of normalization files are created by norm_map. They are described below. The type of file produced is specified by the normalization flag.

OPTIONS
-- Prints a list of all flags and arguments.

-pathdata directory
    The base directory used for finding the data files finput, and fdescribe and for storing the file fparam. A slash "/" is automatically added to the end of the base directory if it doesn't end with a slash.

-finput file
    The ASCII training file in pathdata with the data to be used for normalization. The format and naming conventions for input files are described on the mapper(1) manual page.

-fdescribe file
    This file contains settings for the data base type, the number of input features, labels for the input features, the number of output classes, and labels for the output classes. Description files are described on the mapper(1) manual page.

-fparam file
    Name of a file in pathdata for storing feature search results. This file is written using the routine norm_write_paramfile() found in nnlib.a. It can be read using norm_read_paramfile() or by using the parameter file handling routines in the library nnlib.a. In the LNKmap system, the normalization files are assumed to be named <base>.norm.<norm_type>. Where <base> is the name of the data base and <norm_type> describes which type of normalization parameters are in the file. The types are none, simple, and pca. For example, the principal components parameters for the gauss_map data base are stored in gauss_map.norm.pca.

-normalization n
    n determines which type of normalization file will be created.

    0 none
        Do not do normalization. Create a normalization file which, when applied, will result in the data being left alone.

    1 simple
        Calculate means and variances for each input dimension. When applied, the resulting input patterns have zero mean and unit variance in all dimensions. The default filename for a simple normalization parameter file is <base>.norm.simple. The simple normalization parameter file for the gauss_map data base is gauss_map.norm.simple.

    2 Principal Components Analysis
        PCA assumes that the entire feature set can be modeled as a multivariate Gaussian distribution. PCA finds a linear transformation that uncorrelates the features, or diagonalizes the covariance matrix. The first dimension in the transformed space corresponds to the direction in the original feature space with the greatest variance. The remaining dimensions are orthogonal to the first and correspond to directions of decreasing variance. The default filename for a principal components analysis normalization parameter file is <base>.norm.pca. The PCA normalization file for the gauss_map data base is gauss_map.norm.pca.

-debug n
    The value of n determines the quantity of status messages printed out while norm runs.

-verbose n
    The value of n determines the quantity of status messages printed out while norm runs.

REFERENCES
Charles R. Jankowski, Jr. A Comparison of Auditory Models for Automatic Speech Recognition Master's Thesis, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, Cambridge, MA, May 1992. Pages 27-31.

SEE ALSO
mapper(1)

HISTORY
First written 24 June 1992 by Linda Kukolich

BUGS
Send bug reports to Linda Kukolich (kukolich@sst.ll.mit.edu)