Data Stream Clustering With Affinity Propagation
نویسندگان
چکیده
منابع مشابه
Affinity Propagation, and other Data Clustering Techniques
In our research we sought to create implementations of several common clustering algorithms and a relatively new approach called Affinity Propagation. Our objective was to compare the techniques by running tests on one and two dimensional datasets provided by Professor Trono. Dave Kronenberg implemented a standard randomly seeded K-Means clustering program and many related support functions. We...
متن کاملAffinity Propagation: Clustering Data by Passing Messages
AFFINITY PROPAGATION: CLUSTERING DATA BY PASSING MESSAGES Delbert Dueck Doctor of Philosophy Graduate Department of Electrical & Computer Engineering University of Toronto 2009 Clustering data by identifying a subset of representative examples is important for detecting patterns in data and in processing sensory signals. Such “exemplars” can be found by randomly choosing an initial subset of da...
متن کاملAdaptive Affinity Propagation Clustering
Affinity propagation clustering (AP) has two limitations: it is hard to know what value of parameter ‘preference’ can yield an optimal clustering solution, and oscillations cannot be eliminated automatically if occur. The adaptive AP method is proposed to overcome these limitations, including adaptive scanning of preferences to search space of the number of clusters for finding the optimal clus...
متن کاملData Streaming with Affinity Propagation
This paper proposed StrAP (Streaming AP), extending Affinity Propagation (AP) to data steaming. AP, a new clustering algorithm, extracts the data items, or exemplars, that best represent the dataset using a message passing method. Several steps are made to build StrAP. The first one (Weighted AP) extends AP to weighted items with no loss of generality. The second one (Hierarchical WAP) is conce...
متن کاملSubspace clustering using affinity propagation
This paper proposes a subspace clustering algorithm by introducing attribute weights in the affinity propagation algorithm. A new step is introduced to the affinity propagation process to iteratively update the attribute weights based on the current partition of the data. The relative magnitude of the attribute weights can be used to identify the subspaces in which clusters are embedded. Experi...
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: IEEE Transactions on Knowledge and Data Engineering
سال: 2014
ISSN: 1041-4347
DOI: 10.1109/tkde.2013.146