explicit prequential eval

Author: fracpete

src/main/java/mekaexamples/classifiers/EvaluatePrequential.java

@@ -0,0 +1,55 @@
+/*
+ *   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 <http://www.gnu.org/licenses/>.
+ */
+
+/*
+ * EvaluatePrequential.java
+ * Copyright (C) 2024 University of Waikato, Hamilton, NZ
+ */
+
+package mekaexamples.classifiers;
+
+import meka.classifiers.incremental.IncrementalEvaluation;
+import meka.classifiers.multilabel.incremental.BRUpdateable;
+import meka.core.MLUtils;
+import meka.core.Result;
+import weka.core.Instances;
+import weka.core.converters.ConverterUtils.DataSource;
+
+/**
+ * Evaluates a BRUpdateable Meka classifier prequentially on a dataset supplied by the user.
+ * <br>
+ * Expected parameters: &lt;dataset&gt;
+ * <br>
+ * Note: The dataset must have been prepared for Meka already.
+ *
+ * @author FracPete (fracpete at waikato dot ac dot nz)
+ */
+public class EvaluatePrequential {
+
+  public static void main(String[] args) throws Exception {
+    if (args.length != 1)
+      throw new IllegalArgumentException("Required arguments: <dataset>");
+
+    System.out.println("Loading data: " + args[0]);
+    Instances data = DataSource.read(args[0]);
+    MLUtils.prepareData(data);
+
+    System.out.println("Build BRUpdateable classifier");
+    BRUpdateable classifier = new BRUpdateable();
+    // further configuration of classifier
+    Result result = IncrementalEvaluation.evaluateModelPrequentialBasic(classifier, data, 20, 1.0,"PCut1","3");
+    System.out.println(result);
+  }
+}