@Override public TypeInformation[] getInputTypeRestriction() { // The input relation must match our distance function: return TypeUtil.array(getDistanceFunction().getInputTypeRestriction()); }
@Override public TypeInformation[] getInputTypeRestriction() { // The input relation must match our distance function: return TypeUtil.array(getDistanceFunction().getInputTypeRestriction()); }
@Override public TypeInformation[] getInputTypeRestriction() { // The input relation must match our distance function: return TypeUtil.array(getDistanceFunction().getInputTypeRestriction()); }
DistanceQuery<O> dq = db.getDistanceQuery(relation, getDistanceFunction()); ArrayDBIDs ids = DBIDUtil.ensureArray(relation.getDBIDs()); final int size = ids.size();
LOG.verbose("Notice: SLINK is a much faster algorithm for single-linkage clustering!"); DistanceQuery<O> dq = db.getDistanceQuery(relation, getDistanceFunction()); final DBIDs ids = relation.getDBIDs(); MatrixParadigm mat = new MatrixParadigm(ids);
LOG.verbose("Notice: SLINK is a much faster algorithm for single-linkage clustering!"); DistanceQuery<O> dq = db.getDistanceQuery(relation, getDistanceFunction()); final DBIDs ids = relation.getDBIDs(); MatrixParadigm mat = new MatrixParadigm(ids);
builder.add(ix, linkage.restore(mindist, getDistanceFunction().isSquared()), iy);
builder.add(ix, linkage.restore(mindist, getDistanceFunction().isSquared()), iy);