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https://www.researchgate.net/publication/26621323_Using_Meta-Learning_to_Support_Data_Mining
According to [43], Meta Learning is a very effective tech- nique for solving support data mining. In regression and classification problems Meta Feature (MF) and Meta Learning algorithms have been ...
http://www.tmrfindia.org/ijcsa/V1I13.pdf
Current data mining tools are characterized by a plethora of algorithms but a lack of guidelines to select the right method according to the nature of the problem under analysis. Producing such guidelines is a primary goal by the field of meta-learning; the research objective is to understand the interaction
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.105.1351
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Current data mining tools are characterized by a plethora of algorithms but a lack of guidelines to select the right method according to the nature of the problem under analysis. Producing such guidelines is a primary goal by the field of meta-learning; the research objective is to understand the interaction between ...
https://www.academia.edu/2621174/Using_meta-learning_to_support_data_mining
Abstract: Current data mining tools are characterized by a plethora of algorithms but a lack of guidelines to select the right method according to the nature of the problem under analysis. Producing such guidelines is a primary goal by the field of
http://cui.unige.ch/~kalousis/papers/2014/NguyenEtAl-IJAIR2014-LearningToPlanDMworkflowsWithMetaMining.pdf
the meta-mining models using a similarity learning approach, and extract the workflow descriptors by mining the workflows for generalized relational patterns accounting also for domain knowledge provided by a data mining ontology. We evaluate the quality of the data mining workflows that the system produces on a collection of real world datasets
https://www.researchgate.net/profile/Salvatore_Stolfo/publication/2644008_Meta-Learning_in_Distributed_Data_Mining_Systems_Issues_and_Approaches/links/0fcfd50b220d09d6e1000000/Meta-Learning-in-Distributed-Data-Mining-Systems-Issues-and-Approaches.pdf
Meta-learning in distributed data mining systems: ... over time), extensible to support new and more advanced data mining technologies and last but not least, highly effective. The intent of this ...
https://en.wikipedia.org/wiki/Data_mining
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for ...
https://en.wikipedia.org/wiki/Meta_learning_(computer_science)
Meta learning is a subfield of machine learning where automatic learning algorithms are applied on metadata about machine learning experiments. As of 2017 the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing learning ...
https://www.academia.edu/983680/Using_meta-learning_to_support_data_mining
Using meta-learning to support data mining
http://cui.unige.ch/~kalousis/htmlStaff/Metalearning.htm
Meta-learning and meta-mining. My early days in research were on the area, of what I would call empirical meta-learning, where we were trying to chart the areas of expertise of learning algorithms with respect to dataset characteristics.
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