SEP/COP: an efficient method to find the best partition in hierarchical clustering based on a new cluster validity index Hierarchical clustering algorithms provide a set of nested partitions called a cluster hierarchy. Since the hierarchy is usually too complex it is reduced to a single partition by using cluster validity indices. We show that the classical method is often not useful and we propose SEP, a new method that efficiently searches in an extended partition set. Furthermore, we propose a new cluster validity index, COP, since many of the commonly used indices cannot be used with SEP. Experiments performed with 80 synthetic and 7 real datasets confirm that SEP/COP is superior to the method currently used and furthermore, it is less sensitive to noise.