Scaling up classification rule induction through parallel processing
نویسندگان
چکیده
منابع مشابه
Scaling up classification rule induction through parallel processing
The fast increase in the size and number of databases demands data mining approaches that are scalable to large amounts of data. This has led to the exploration of parallel computing technologies in order to perform data mining tasks concurrently using several processors. Parallelization seems to be a natural and cost-effective way to scale up data mining technologies. One of the most important...
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Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unseen data. Alternative algorithms have been developed such as the Prism algorithm. Prism constructs modular rules which produce qualitatively better rules than rules induced by TDIDT. However, along with the increasing ...
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ژورنال
عنوان ژورنال: The Knowledge Engineering Review
سال: 2012
ISSN: 0269-8889,1469-8005
DOI: 10.1017/s0269888912000355