Skip feature when classifying, but show feature in output

Question

I\'ve created a dataset which contains +/- 13000 rows with +/- 50 features. I know how to output every classification result: prediction and actual, but I would like to be able

Answer 1

Let's say follwoing are the attributes in the bbcsport.arff that you want to remove and is in a file attributes.txt line by line..

serena
serve
service
sets
striking
tennis
tiebreak
tournaments
wimbledon
..
Here is how you may include or exclude the attributes by setting true or false. (mutually elusive) remove.setInvertSelection(false)

BufferedReader datafile = new BufferedReader(new FileReader("bbcsport.arff")); 
BufferedReader attrfile = new BufferedReader(new FileReader("attributes.txt"));

Instances data = new Instances(datafile); 
List<Integer> myList = new ArrayList<Integer>();
String line;

while ((line = attrfile.readLine()) != null) {
  for (n = 0; n < data.numAttributes(); n++) {
    if (data.attribute(n).name().equalsIgnoreCase(line)) {
      if(!myList.contains(n)) 
        myList.add(n); 
    } 
  }
}

int[] attrs = myList.stream().mapToInt(i -> i).toArray();
Remove remove = new Remove();
remove.setAttributeIndicesArray(attrs);
remove.setInvertSelection(false);
remove.setInputFormat(data); // init filter

Instances filtered = Filter.useFilter(data, remove);

'filtered' has the final attributes..

My blog .. http://ojaslabs.com/include-exclude-attributes-in-weka

Answer 2

Use FilteredClassifier. See this and this .