线性判别分析

我被要求对我的一个项目的一组数据进行线性判别分析。我正在使用ALGLIB (c++版本)，它有一个渔场函数，但我需要一些帮助了解如何使用它。

用户回答了一组6个问题(答案是1-7之间的数字)，这给了我一个示例数据集，例如{1,2,3,4,5,6}。然后我有5类，每类6个值，例如{0.765,0.895,1.345,2.456,0.789,5.678}。fisher lda函数接受一个二维的值数组，并返回另一个一维的值数组(我不知道它们是什么意思)。

据我所知，我需要看看哪个类的用户回答最适合?

如果能帮助我理解LDA和/或如何使用这个函数，我将不胜感激。

下面是我要使用的函数的定义:

/*************************************************************************
Multiclass Fisher LDA
Subroutine finds coefficients of linear combination which optimally separates
training set on classes.
INPUT PARAMETERS:
    XY          -   training set, array[0..NPoints-1,0..NVars].
                    First NVars columns store values of independent
                    variables, next column stores number of class (from 0
                    to NClasses-1) which dataset element belongs to. Fractional
                    values are rounded to nearest integer.
    NPoints     -   training set size, NPoints>=0
    NVars       -   number of independent variables, NVars>=1
    NClasses    -   number of classes, NClasses>=2

OUTPUT PARAMETERS:
    Info        -   return code:
                    * -4, if internal EVD subroutine hasn't converged
                    * -2, if there is a point with class number
                          outside of [0..NClasses-1].
                    * -1, if incorrect parameters was passed (NPoints<0,
                          NVars<1, NClasses<2)
                    *  1, if task has been solved
                    *  2, if there was a multicollinearity in training set,
                          but task has been solved.
    W           -   linear combination coefficients, array[0..NVars-1]
  -- ALGLIB --
     Copyright 31.05.2008 by Bochkanov Sergey
*************************************************************************/
void fisherlda(const real_2d_array &xy, const ae_int_t npoints, const ae_int_t nvars, const ae_int_t nclasses, ae_int_t &info, real_1d_array &w);