document: YALE : rapid prototyping for complex data mining tasks KDD is a complex and demanding task . While a large number of methods has been established for numerous problems , many challenges remain to be solved . New tasks emerge requiring the development of new methods or processing schemes . Like in software development , the development of such solutions demands for careful analysis , specification , implementation , and testing . Rapid prototyping is an approach which allows crucial design decisions as early as possible . A rapid prototyping system should support maximal re-use and innovative combinations of existing methods , as well as simple and quick integration of new ones . This paper describes Yale , a free open-source environment forKDD and machine learning . Yale provides a rich variety of methods whichallows rapid prototyping for new applications and makes costlyre-implementations unnecessary . Additionally , Yale offers extensive functionality for process evaluation and optimization which is a crucial property for any KDD rapid prototyping tool . Following the paradigm of visual programming eases the design of processing schemes . While the graphical user interface supports interactive design , the underlying XML representation enables automated applications after the prototyping phase . After a discussion of the key concepts of Yale , we illustrate the advantages of rapid prototyping for KDD on case studies ranging from data pre-processing to result visualization . These case studies cover tasks like feature engineering , text mining , data stream mining and tracking drifting concepts , ensemble methods and distributed data mining . This variety of applications is also reflected in a broad user base , we counted more than 40,000 downloads during the last twelve months .
doc_bio_tags: 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 B I O O O O O O O O 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 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 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 B I O O O O O O O O O O B I O O O O O O O O O O O O O B I I O O O O O O O O B I 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