/** * Clears the stack, reseting its capacity to the default. */ public void clear() { _list.clear(DEFAULT_CAPACITY); }
/** * Flushes the internal state of the list, resetting the capacity * to the default. */ public void clear() { clear(DEFAULT_CAPACITY); }
public void clear() { included.clear(); }
public void clear() { included.clear(); }
public void clear() { included.clear(); }
public void initializeClusters(IWeighting3D dists, Centroid[] centroids) { Random r = new Random(); boolean[] assigned = new boolean[dists.getFirstDimensionSize()]; // Choose k random centroids. for (int i = 0; i < centroids.length; i++) { centroids[i].documents.clear(); int next = r.nextInt(dists.getFirstDimensionSize()); int idx = -1; if (assigned[next]) { for (int doc = (next + 1) % assigned.length; doc != next; doc = (doc + 1) % assigned.length) { if (!assigned[doc]) { assigned[doc] = true; idx = doc; break; } } } else { idx = next; assigned[idx] = true; } centroids[i].documents.add((short) idx); } // Update centroid for each cluster. for (int i = 0; i < centroids.length; i++) centroids[i].computeCentroid(dists); }
public void beginEvaluation(IIntIterator documents, IIndex index) { _assignments.clear(); documents.begin(); while (documents.hasNext()) { documents.next(); _assignments.add(-1); } _documents = documents; _index = index; }
public void initializeClusters(IWeighting3D dists, Centroid[] centroids) { TreeSet<CategoryItem> ordered = new TreeSet<CategoryItem>(); IShortIterator categories = _index.getCategoryDB().getCategories(); while (categories.hasNext()) { short catID = categories.next(); int positives = _index.getClassificationDB().getCategoryDocumentsCount(catID); CategoryItem ci = new CategoryItem(); ci.catID = catID; ci.positives = positives; ordered.add(ci); } Iterator<CategoryItem> items = ordered.iterator(); // Choose k random centroids. for (int i = 0; i < centroids.length; i++) { centroids[i].documents.clear(); CategoryItem ci = items.next(); centroids[i].documents.add(ci.catID); } // Update centroid for each cluster. for (int i = 0; i < centroids.length; i++) centroids[i].computeCentroid(dists); }
centroids[i].documents.clear(); FeatureItem ci = items.next(); centroids[i].documents.add(ci.featureID);
centroids[i].documents.clear();
while (toUpdate) { for (int i = 0; i < centroids.length; i++) { centroids[i].documents.clear();
ids.clear(); int previous = -1; for(int i : _tmp)
ids.clear(); int previous = -1; for(int i : _tmp)
if (gsize > maxFeatsPerGroup) { maxFeatsPerGroup = gsize; maxFeatsPerGroupGroups.clear(); maxFeatsPerGroupGroups.add(i);
while (toUpdate) { for (int i = 0; i < centroids.length; i++) { centroids[i].documents.clear(); centroids[i].distances.clear();