VB Principal Component Example

Imports System
Imports Microsoft.VisualBasic

Imports CenterSpace.NMath.Core

Imports System.IO

Namespace CenterSpace.NMath.Examples.VisualBasic

  A .NET example in Visual Basic showing how to perform a principal component analysis on a data set.
  Module PrincipalComponentExample

    Sub Main()

      Read in data from a file. These data give air pollution and related values
      for 41 U.S. cities.
        SO2: Sulfur dioxide content of air in micrograms per cubic meter 
        Temp: Average annual temperature in degrees Fahrenheit 
        Man: Number of manufacturing enterprises employing 20 or more workers 
        Pop: Population size in thousands from the 1970 census 
        Wind: Average annual wind speed in miles per hour 
        Rain: Average annual precipitation in inches 
        RainDays: Average number of days with precipitation per year 
      Source: http://lib.stat.cmu.edu/DASL/Datafiles/AirPollution.html

      Dim DF As DataFrame = DataFrame.Load("PrincipalComponentExample.dat", True, True, ControlChars.Tab, True)

      Console.WriteLine()
      Console.WriteLine(DF)
      Console.WriteLine()

      Class DoublePCA performs a double-precision principal component
      analysis on a given data set. The data may optionally be centered and
      scaled before analysis takes place. By default, variables are centered
      but not scaled.
      Dim PCA As New DoublePCA(DF)

      Once your data is analyzed, you can can retrieve information about the data.
      If centering was specified, the column means are subtracted from
      the column values before analysis takes place. If scaling was specified,
      column values are scaled to have unit variance before analysis by dividing
      by the column norm.
      Console.WriteLine("Number of Observations = " & PCA.NumberOfObservations)
      Console.WriteLine("Number of Variables = " & PCA.NumberOfVariables)
      Console.WriteLine()
      Console.WriteLine("Column Means = " & PCA.Means.ToString("G5"))
      Console.WriteLine()
      Console.WriteLine("Column Norms = " & PCA.Norms.ToString("G5"))
      Console.WriteLine()
      Console.WriteLine("Data was centered? = " & PCA.IsCentered)
      Console.WriteLine("Data was scaled? = " & PCA.IsScaled)
      Console.WriteLine()

      The Loadings property gets the loading matrix. Each column is a principal component.
      Console.WriteLine("Loadings =")
      Console.WriteLine(PCA.Loadings.ToTabDelimited("G9"))
      Console.WriteLine()

      You can retrieve a particular principal component using the indexer.
      Console.WriteLine("First principal component = " & PCA(0).ToString("G5"))
      Console.WriteLine()
      Console.WriteLine("Second principal component = " & PCA(1).ToString("G5"))
      Console.WriteLine()

      The first principal component accounts for as much of the variability in the
      data as possible, and each succeeding component accounts for as much of the
      remaining variability as possible.
      Console.WriteLine("Variance Proportions = " & PCA.VarianceProportions.ToString("G5"))
      Console.WriteLine()
      Console.WriteLine("Cumulative Variance Proportions = " & PCA.CumulativeVarianceProportions.ToString("G9"))
      Console.WriteLine()

      You can also get the number of principal components required to account for
      a given proportion of the total variance. In this case, a plane fit to the
      original 7-dimensional space accounts for 99% of the variance.
      Console.WriteLine("PCs that account for 99% of the variance = " & PCA.Threshold(0.99))
      Console.WriteLine()

      The Score matrix is the data formed by transforming the original data into
      the space of the principal components.
      Console.WriteLine("Scores =")
      Console.WriteLine(PCA.Scores.ToTabDelimited("G9"))

      Console.WriteLine()
      Console.WriteLine("Press Enter Key")
      Console.Read()

    End Sub

  End Module

End Namespace