Documentation of 'org.encog.app.analyst.csv.normalize.AnalystNormalizeCSV' Java class
AnalystNormalizeCSV
org.encog.app.analyst.csv.normalize

Class AnalystNormalizeCSV

  • All Implemented Interfaces:
    QuantTask


    public class AnalystNormalizeCSV
    extends BasicFile
    Normalize, or denormalize, a CSV file.
    • Constructor Detail

      • AnalystNormalizeCSV

        public AnalystNormalizeCSV()
    • Method Detail

      • extractFields

        public static final double[] extractFields(EncogAnalyst analyst,
                                                   CSVHeaders headers,
                                                   ReadCSV csv,
                                                   int outputLength,
                                                   boolean skipOutput)
        Extract fields from a file into a numeric array for machine learning.
        Parameters:
        analyst - The analyst to use.
        headers - The headers for the input data.
        csv - The CSV that holds the input data.
        outputLength - The length of the returned array.
        skipOutput - True if the output should be skipped.
        Returns:
        The encoded data.
      • analyze

        public void analyze(java.io.File inputFilename,
                            boolean expectInputHeaders,
                            CSVFormat inputFormat,
                            EncogAnalyst theAnalyst)
        Analyze the file.
        Parameters:
        inputFilename - The input file.
        expectInputHeaders - True, if input headers are present.
        inputFormat - The format.
        theAnalyst - The analyst to use.
      • normalize

        public void normalize(java.io.File file)
        Normalize the input file. Write to the specified file.
        Parameters:
        file - The file to write to.
      • setSourceFile

        public void setSourceFile(java.io.File file,
                                  boolean headers,
                                  CSVFormat format)
        Set the source file. This is useful if you want to use pre-existing stats to normalize something and skip the analyze step.
        Parameters:
        file - The file to use.
        headers - True, if headers are to be expected.
        format - The format of the CSV file.

DMelt 3.0 © DataMelt by jWork.ORG

You see the box below because you did not login.