public int shrink(float threshold) {
int[] indexMap = new int[getFeatureSize()];
int i, j, k, l, count = 1; // bias
float max, min;
for (i = 1; i < getFeatureSize(); i++) {
k = i * getLabelSize();
max = weight_vector.get(k);
min = weight_vector.get(k);
for (j = 1; j < getLabelSize(); j++) {
max = Math.max(max, weight_vector.get(k + j));
min = Math.min(min, weight_vector.get(k + j));
}
if (Math.abs(max - min) >= threshold) indexMap[i] = count++;
}
WeightVector newWeights =
new WeightVectorDynamic(
weight_vector.getLabelSize(), count, weight_vector.getActivationFunction());
ObjectIterator<Entry<String, Integer>> it;
int oldIndex, newIndex;
Entry<String, Integer> e;
// bias weights
for (j = 0; j < getLabelSize(); j++) newWeights.set(j, weight_vector.get(j));
for (Object2IntMap<String> map : feature_map.getIndexMaps()) {
it = map.entrySet().iterator();
while (it.hasNext()) {
e = it.next();
oldIndex = e.getValue();
newIndex = indexMap[oldIndex];
if (newIndex > 0) {
e.setValue(newIndex);
k = oldIndex * getLabelSize();
l = newIndex * getLabelSize();
for (j = 0; j < getLabelSize(); j++) newWeights.set(l + j, weight_vector.get(k + j));
} else it.remove();
}
}
weight_vector = newWeights;
feature_map.setSize(count);
return count;
}
