Tham khảo tài liệu 'data analysis machine learning and applications episode 2 part 4', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | A Pattern Based Data Mining Approach 333 2. Science converges. Concepts in one area of science is applicable in another area. Patterns support these processes. This potential is comparable to the promises of Systems Theory. 3. Decision for a specific algorithm can be postponed to later stages. A solution path as a whole will be sketched through patterns and algorithms need only be filled in immediately prior to processing. Using differnet algorithms in places will not invalidate the solution path creating late binding at the algorithm level. Current Data Mining applications occasionally provide the user with first traces of pattern based DM. Figure 5 shows the example of Bagging of Classifiers within the TANAGRA project and its graphical user interface Rakotomalala 2004 . Bagging cannot be described with a pure data flow paradigm rather a nesting of a classifier pattern within the bagging pattern is needed. This nested structure will then be pipelined with pre- and postprocessing patterns. Fig. 5. Screenshot of Tanagra Software Further steps in our project are to collect a list of patterns which are useful in the whole knowledge discovery process and data mining list will be open-ended . integrate these patterns into data mining software to help design ad-hoc algorithms choose an existing one or have guidance in the data mining process. develop a software prototype with our pattern and make experiments with users how it works and what are the benefits. 334 Boris Delibasic Kathrin Kirchner and Johannes Ruhland References ALEXANDER C. 1979 The Timeless Way of Building Oxford University Press. ALEXANDER C. 2002a The Nature of Order Book 1 The Phenomenon of Life The Center for Environmental Structure Berkeley California. ALEXANDER C. 2002b The Nature of Order Book 2 The Process of Creating Life The Center for Environmental Structure Berkeley California. CHAPMAN P. CLINTON J. KERBER R. KHABAZA T. REINARTZ T. SHEARER C. and WIRTH R. 2000 CRISP-DM . Step-by-step data .
