A roadmap to multifactor dimensionality reduction methods
نویسندگان
چکیده
منابع مشابه
A roadmap to multifactor dimensionality reduction methods
Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions. To analyze interactions in genetic data, many statistical methods have been suggested, with most of them relying on statistical regression models. Given the known limitations of classical methods, approaches from the machine-learning community have also become attractive...
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In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (...
متن کاملTitle : An R Package Implementation of Multifactor Dimensionality Reduction
abstracts should not cite references, nor refer to figures or tables. The reference to Ritchie et al 2001 has been removed from the abstract on Page 2. Minor revisions (we can make these changes for you, although it will speed up publication of your manuscript if you do them while making the major changes above) Author Contributions: Please confirm that all authors read and approved the final m...
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BACKGROUND Common complex traits may involve multiple genetic and environmental factors and their interactions. Many methods have been proposed to identify these interaction effects, among them several machine learning and data mining methods. These are attractive for identifying interactions because they do not rely on specific genetic model assumptions. To handle the computational burden aris...
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When data sets are multilevel (group nesting or repeated measures), different sources of variations must be identified. In the framework of unsupervised analyses, multilevel simultaneous component analysis (MSCA) has recently been proposed as the most satisfactory option for analyzing multilevel data. MSCA estimates submodels for the different levels in data and thereby separates the “within”-s...
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ژورنال
عنوان ژورنال: Briefings in Bioinformatics
سال: 2015
ISSN: 1467-5463,1477-4054
DOI: 10.1093/bib/bbv038