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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This version represents the developer version, the
"bleeding edge" of development, you could say. New functionality gets added
to this version.
/*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see -mean-prec <int>
* The number of decimals after the decimal point for the mean.
* (default: 2)
*
* -stddev-prec <int>
* The number of decimals after the decimal point for the mean.
* (default: 2)
*
* -col-name-width <int>
* The maximum width for the column names (0 = optimal).
* (default: 0)
*
* -row-name-width <int>
* The maximum width for the row names (0 = optimal).
* (default: 40)
*
* -mean-width <int>
* The width of the mean (0 = optimal).
* (default: 0)
*
* -stddev-width <int>
* The width of the standard deviation (0 = optimal).
* (default: 0)
*
* -sig-width <int>
* The width of the significance indicator (0 = optimal).
* (default: 0)
*
* -count-width <int>
* The width of the counts (0 = optimal).
* (default: 0)
*
* -show-stddev
* Whether to display the standard deviation column.
* (default: no)
*
* -show-avg
* Whether to show the row with averages.
* (default: no)
*
* -remove-filter
* Whether to remove the classname package prefixes from the
* filter names in datasets.
* (default: no)
*
* -print-col-names
* Whether to output column names or just numbers representing them.
* (default: no)
*
* -print-row-names
* Whether to output row names or just numbers representing them.
* (default: no)
*
* -enum-col-names
* Whether to enumerate the column names (prefixing them with
* '(x)', with 'x' being the index).
* (default: no)
*
* -enum-row-names
* Whether to enumerate the row names (prefixing them with
* '(x)', with 'x' being the index).
* (default: no)
*
*
* @author FracPete (fracpete at waikato dot ac dot nz)
* @version $Revision: 8034 $
*/
public class ResultMatrixSignificance
extends ResultMatrix {
/** for serialization. */
private static final long serialVersionUID = -1280545644109764206L;
/**
* initializes the matrix as 1x1 matrix.
*/
public ResultMatrixSignificance() {
this(1, 1);
}
/**
* initializes the matrix with the given dimensions.
*
* @param cols the number of columns
* @param rows the number of rows
*/
public ResultMatrixSignificance(int cols, int rows) {
super(cols, rows);
}
/**
* initializes the matrix with the values from the given matrix.
*
* @param matrix the matrix to get the values from
*/
public ResultMatrixSignificance(ResultMatrix matrix) {
super(matrix);
}
/**
* Returns a string describing the matrix.
*
* @return a description suitable for
* displaying in the experimenter gui
*/
public String globalInfo() {
return "Only outputs the significance indicators. Can be used for spotting patterns.";
}
/**
* returns the name of the output format.
*
* @return the display name
*/
public String getDisplayName() {
return "Significance only";
}
/**
* returns the default of whether column names or numbers instead are printed.
*
* @return true if names instead of numbers are printed
*/
public boolean getDefaultPrintColNames() {
return false;
}
/**
* returns the default width for the row names.
*
* @return the width
*/
public int getDefaultRowNameWidth() {
return 40;
}
/**
* returns the default of whether std deviations are displayed or not.
*
* @return true if the std deviations are displayed
*/
public boolean getDefaultShowStdDev() {
return false;
}
/**
* sets whether to display the std deviations or not - always false!
*
* @param show ignored
*/
public void setShowStdDev(boolean show) {
// ignore
}
/**
* returns the matrix as plain text.
*
* @return the matrix
*/
public String toStringMatrix() {
StringBuffer result;
String[][] cells;
int i;
int n;
int nameWidth;
String line;
String colStr;
int rows;
result = new StringBuffer();
cells = toArray();
// pad names
nameWidth = getColSize(cells, 0);
for (i = 0; i < cells.length - 1; i++)
cells[i][0] = padString(cells[i][0], nameWidth);
// determine number of displayed rows
rows = cells.length - 1;
if (getShowAverage())
rows--;
for (i = 0; i < rows; i++) {
line = "";
colStr = "";
for (n = 0; n < cells[i].length; n++) {
// the header of the column
if (isMean(n) || isRowName(n))
colStr = cells[0][n];
if ( (n > 1) && (!isSignificance(n)) )
continue;
// padding between cols
if (n > 0)
line += " ";
// padding for "(" below dataset line
if ( (i > 0) && (n > 1) )
line += " ";
if (i == 0) {
line += colStr;
}
else {
if (n == 0) {
line += cells[i][n];
}
else if (n == 1) {
line += colStr.replaceAll(".", " "); // base column has no significance!
}
else {
line += cells[i][n];
// add blanks dep. on length of #
line += colStr.replaceAll(".", " ").substring(2);
}
}
}
result.append(line + "\n");
// separator line
if (i == 0)
result.append(line.replaceAll(".", "-") + "\n");
}
return result.toString();
}
/**
* returns the header of the matrix as a string.
*
* @return the header
* @see #m_HeaderKeys
* @see #m_HeaderValues
*/
public String toStringHeader() {
return new ResultMatrixPlainText(this).toStringHeader();
}
/**
* returns returns a key for all the col names, for better readability if
* the names got cut off.
*
* @return the key
*/
public String toStringKey() {
return new ResultMatrixPlainText(this).toStringKey();
}
/**
* returns the summary as string.
*
* @return the summary
*/
public String toStringSummary() {
return new ResultMatrixPlainText(this).toStringSummary();
}
/**
* returns the ranking in a string representation.
*
* @return the ranking
*/
public String toStringRanking() {
return new ResultMatrixPlainText(this).toStringRanking();
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 8034 $");
}
/**
* for testing only.
*
* @param args ignored
*/
public static void main(String[] args) {
ResultMatrix matrix;
int i;
int n;
matrix = new ResultMatrixSignificance(3, 3);
// set header
matrix.addHeader("header1", "value1");
matrix.addHeader("header2", "value2");
matrix.addHeader("header2", "value3");
// set values
for (i = 0; i < matrix.getRowCount(); i++) {
for (n = 0; n < matrix.getColCount(); n++) {
matrix.setMean(n, i, (i+1)*n);
matrix.setStdDev(n, i, ((double) (i+1)*n) / 100);
if (i == n) {
if (i % 2 == 1)
matrix.setSignificance(n, i, SIGNIFICANCE_WIN);
else
matrix.setSignificance(n, i, SIGNIFICANCE_LOSS);
}
}
}
System.out.println("\n\n--> " + matrix.getDisplayName());
System.out.println("\n1. complete\n");
System.out.println(matrix.toStringHeader() + "\n");
System.out.println(matrix.toStringMatrix() + "\n");
System.out.println(matrix.toStringKey());
System.out.println("\n2. complete with std deviations\n");
matrix.setShowStdDev(true);
System.out.println(matrix.toStringMatrix());
System.out.println("\n3. cols numbered\n");
matrix.setPrintColNames(false);
System.out.println(matrix.toStringMatrix());
System.out.println("\n4. second col missing\n");
matrix.setColHidden(1, true);
System.out.println(matrix.toStringMatrix());
System.out.println("\n5. last row missing, rows numbered too\n");
matrix.setRowHidden(2, true);
matrix.setPrintRowNames(false);
System.out.println(matrix.toStringMatrix());
System.out.println("\n6. mean prec to 3\n");
matrix.setMeanPrec(3);
matrix.setPrintRowNames(false);
System.out.println(matrix.toStringMatrix());
}
}
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