This document describes the hierarchical agglomerative cluster algorithm Pnc 2 in the context of direct generation of If-Then rules for classification tasks. As an agglomerative cluster algorithm, the Pnc 2 initializes each learn data tuple as a single cluster. Then, if a merge test is passed, iteratively always those two clusters with the same output value are merged, that are closest to each other. The merge test transforms the generalized cluster into a rule and evaluates it by a kind of hitrate. The rule's premise is the cuboid, that encloses the input vectors of all learn data tuples merged in the cluster. This representation su#ers in high dimensional input spaces due to the COD problem and thus a special mechanism is used to extend the cuboid during the merge test.