Encoding dissimilarity data for statistical model building
نویسندگان
چکیده
منابع مشابه
Encoding Dissimilarity Data for Statistical Model Building.
We summarize, review and comment upon three papers which discuss the use of discrete, noisy, incomplete, scattered pairwise dissimilarity data in statistical model building. Convex cone optimization codes are used to embed the objects into a Euclidean space which respects the dissimilarity information while controlling the dimension of the space. A "newbie" algorithm is provided for embedding n...
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We explore three papers concerned with two methods for incorporating discrete, noisy, incomplete dissimilarity data into statistical/machine learning models for supervised, semisupervised or unsupervised machine learning. The two methods are RKE (Regularized Kernel Estimation), and RMU (Regularized Manifold Unfolding). Briefly put, the methods use dissimilarity information between objects in a ...
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ژورنال
عنوان ژورنال: Journal of Statistical Planning and Inference
سال: 2010
ISSN: 0378-3758
DOI: 10.1016/j.jspi.2010.04.025