Semi-supervised model-based clustering with controlled clusters leakage
نویسندگان
چکیده
منابع مشابه
Semi-supervised model-based clustering with controlled clusters leakage
In this paper, we focus on finding clusters in partially categorized data sets. We propose a semi-supervised version of Gaussian mixture model, called C3L, which retrieves natural subgroups of given categories. In contrast to other semi-supervised models, C3L is parametrized by user-defined leakage level, which controls maximal inconsistency between initial categorization and resulting clusteri...
متن کاملClassifying GABAergic interneurons with semi-supervised projected model-based clustering
OBJECTIVES A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names. We sought to automatically classify digitally reconstructed interneuronal morphologies according to this scheme. Simultaneously, we sought to discover possible subtypes of these types that might emerge during automatic classification (clustering). We also investigated which morphometric prope...
متن کاملModel Selection for Semi-Supervised Clustering
Although there is a large and growing literature that tackles the semi-supervised clustering problem (i.e., using some labeled objects or cluster-guiding constraints like “must-link” or “cannot-link”), the evaluation of semi-supervised clustering approaches has rarely been discussed. The application of cross-validation techniques, for example, is far from straightforward in the semi-supervised ...
متن کاملFeature Selection based Semi-Supervised Subspace Clustering
Clustering is the process which is used to assign a set of n objects into clusters(groups). Dimensionality reduction techniques help in increasing the accuracy of clustering results by removing redundant and irrelevant dimensions. But, in most of the situations, objects can be related in different ways in different subsets of the dimensions. Dimensionality reduction tends to get rid of such rel...
متن کاملSemi-supervised Clustering
Clustering is an unsupervised learning problem whose objective is to find a partition of the given data. However, a major challenge in clustering is to define an appropriate objective function in order to to find an optimal partition that is useful to the user. To facilitate data clustering, it has been suggested that the user provide some supplementary information about the data (eg. pairwise ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Expert Systems with Applications
سال: 2017
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2017.05.032