private static Map<String, Double> sortByComparator(
Map<String, Double> map, final boolean order) {
List<Entry<String, Double>> list = new LinkedList<Entry<String, Double>>(map.entrySet());
// Sorting the list based on values
Collections.sort(
list,
new Comparator<Entry<String, Double>>() {
public int compare(Entry<String, Double> o1, Entry<String, Double> o2) {
if (order) {
return o1.getValue().compareTo(o2.getValue());
} else {
return o2.getValue().compareTo(o1.getValue());
}
}
});
// Maintaining insertion order with the help of LinkedList
Map<String, Double> sortedMap = new LinkedHashMap<String, Double>();
for (Entry<String, Double> entry : list) {
sortedMap.put(entry.getKey(), entry.getValue());
}
return sortedMap;
}
public static void RetrieveTestMatrix() {
try {
BufferedReader flrdr =
new BufferedReader(
new FileReader("D:\\IR\\Assignment7\\Pytest\\part2\\output\\test_matrix.txt"));
String line = "";
while ((line = flrdr.readLine()) != null) {
SortedSet<Integer> word_ids = new TreeSet<Integer>();
int val_count = 0;
String[] key_value = line.split(" :: ");
if (key_value[1].trim().length() < 1)
System.out.println("Error on Train Doc " + key_value[0]);
key_value[1] = key_value[1].substring(1, key_value[1].length() - 2);
String[] values = key_value[1].split(",");
FeatureNode[] node = new FeatureNode[values.length];
for (String val : values) word_ids.add(Integer.parseInt(val.trim()));
for (int val : word_ids) node[val_count++] = new FeatureNode(val, 1);
double predict = Linear.predict(model, node);
doc_score.put(key_value[0].trim(), predict);
}
flrdr.close();
} catch (Exception e) {
e.printStackTrace();
System.exit(0);
}
}