document: Turning CARTwheels : an alternating algorithm for mining redescriptions We present an unusual algorithm involving classification trees -- CARTwheels -- where two trees are grown in opposite directions so that they are joined at their leaves . This approach finds application in a new data mining task we formulate , called redescription mining . A redescription is a shift-of-vocabulary , or a different way of communicating information about a given subset of data ; the goal of redescription mining is to find subsets of data that afford multiple descriptions . We highlight the importance of this problem in domains such as bioinformatics , which exhibit an underlying richness and diversity of data descriptors ( e.g. , genes can be studied in a variety of ways ) . CARTwheels exploits the duality between class partitions and path partitions in an induced classification tree to model and mine redescriptions . It helps integrate multiple forms of characterizing datasets , situates the knowledge gained from one dataset in the context of others , and harnesses high-level abstractions for uncovering cryptic and subtle features of data . Algorithm design decisions , implementation details , and experimental results are presented .
doc_bio_tags: O O O O O O O O B O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O