Study on Modeling and Algorithm of Optimal Machine Learning Problems in a Group View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2013-2016

FUNDING AMOUNT

720000 CNY

ABSTRACT

Learning the rule of selecting the best one from group data (SBG) is a new machine learning problem. It brings some challenges for the existing machine learning models because of the new characteristics. To eliminate the negative impact on the comparison of the samples with same type between groups, this project first investigates the data preprocessing method,as well as the embedding methods in modeling without taking the comparison. Then, the quantitative measure of generalization performance for SBG is proposed. And some new models for the SBG learning problem are developed, in which a strong generalization performance and a good suitability for nonlinear separable problem within-group are guaranteed. Thirdly,to overcome the extremely unbalanced problem between the sizes of two classes, some methods without utilizing the weights of classes are investigated. Fourthly, the efficient algorithm for the new models with large scale data is presented after investigating the nature of the models. Finally, two applications on the optimizations of process parameters and investment are provided. SBG is a new foundation machine learning problem, this project will extend the models, algorithms and application ranges of the existing machine learning techinique,which is innovation in theory and has great application value. More... »

URL

http://npd.nsfc.gov.cn/projectDetail.action?pid=61271337

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