Changeset 36824

Timestamp:

2022-10-17T16:13:53+13:00 (19 months ago)

Author:

davidb

Message:

Next step in developing knn calculation for sampel AV input

File:

• gs3-installations/mars/trunk/sites/mars/src/java/org/greenstone/mars/WekaFindInstanceKNN.java (modified) (5 diffs)

gs3-installations/mars/trunk/sites/mars/src/java/org/greenstone/mars/WekaFindInstanceKNN.java

@@ -1 +1 @@
 package org.greenstone.mars;
 
+import weka.core.DenseInstance;
 import weka.core.Instance;
 import weka.core.Instances;
@@ -11 +12 @@
 // Based on StackOverflow:
 //   https://stackoverflow.com/questions/31350506/how-to-calculate-the-nearest-neighbors-using-weka-from-the-command-line
+
+// The following was also useful as a reference:
+//    https://waikato.github.io/weka-blog/posts/2018-10-08-making-a-weka-classifier/
 
 public class WekaFindInstanceKNN 
@@ -37 +41 @@
     }
 
-    public static void findNearestKNN(NearestNeighbourSearch knn, Instance sample_instance, int k_nearest)
+    public static void printNearestKNN(Instance sample_instance, Instances nearest_instances, 
+                      int k_nearest)
     {
     try {
-        Instances nearest_instances= knn.kNearestNeighbours(sample_instance, k_nearest);
-        
         //cycle through the instances and printout the nearestneighbors
-        
+
         System.out.println("\n" + sample_instance);
         for(int i =0; i<k_nearest; i++) {
-        System.out.println("\t" + nearest_instances.instance(i));        
+        System.out.println("\t" + nearest_instances.instance(i));
         }   
     }
@@ -57 +60 @@
 
     public static void main(String[] args)
-    {   
+    {
+    // First example output, when working through the instances specified in the CSV file
+    // (looking for similaries amongst all the instances in the CSV file)
+
+    // ds_22716_5743-6,-0.549489,-0.118439
+    //    ds_22761_1171-12,-0.549489,-0.118439
+    //    ds_21046_7743-30,-0.549489,-0.118439
+    //    ds_24768_23507-6,-0.549489,-0.118439
+    //    ds_22761_1171-15,-0.549489,-0.118439
+
     if (args.length != 2) {
         System.err.println("Usage: k-nearest-num file.{arff,csv}");
@@ -74 +86 @@
     NearestNeighbourSearch knn = initKNN(instances);
 
-    /*
-    DataSource source = new DataSource(input_filename);
-    Instances instances = source.getDataSet();
-    
-    LinearNNSearch knn = new LinearNNSearch(instances);
-    //KDTree knn = new KDTree(instances);
-    */
 
-    //cycle through the dataset and get instances for the nearestneighbors
-    
+    Instance sample_instance = new DenseInstance(3);
+    sample_instance.setDataset(instances);
+
+    // sample sample:
+    //   ds_22716_5743-6,-0.549489,-0.118439
+    sample_instance.setValue(0, "ds_22716_5743-6");
+    sample_instance.setValue(1, -0.549489);
+    sample_instance.setValue(2, -0.118439);
+
+    //findNearestKNN(knn,sample_instance,k_nearest);
+
+    try {
+        Instances nearest_instances= knn.kNearestNeighbours(sample_instance, k_nearest);
+        System.out.println("**** nearest_instances len = " + nearest_instances.numInstances());
+
+        printNearestKNN(sample_instance,nearest_instances, k_nearest);
+
+    }
+    catch (Exception e) {
+        e.printStackTrace();
+    }
+
+
+    /*  
     int num_instances = instances.numInstances();
     for(int j=0; j<num_instances; j++) {
-        //Instances nearestInstances= knn.kNearestNeighbours(instances.instance(j), k_nearest);
         
         Instance sample_instance = instances.instance(j);
         findNearestKNN(knn,sample_instance,k_nearest);
-    }    
+        }   
+    */
+ 
     }
 }