Learning Topology of Curves with Application to Clustering
نویسندگان
چکیده
We propose a method for learning the intrinsic topology of a point set sampled from a curve embedded in a high-dimensional ambient space. Our approach does not rely on distances in the ambient space, and thus can recover the topology of sparsely sampled curves, a situation where extant manifold learning methods are expected to fail. We formulate a loss function based on the smoothness of a curve, and derive a greedy procedure for minimizing this loss function. We compare the efficacy of our approach with representative manifold learning and hierarchical clustering methods on both real and synthetic data.
منابع مشابه
Multi-layer Clustering Topology Design in Densely Deployed Wireless Sensor Network using Evolutionary Algorithms
Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...
متن کاملThe Application of Combined Fuzzy Clustering Model and Neural Networks to Measure Valuably of Bank Customers
Currently, acquisition of resources in banks is subject to attraction of the resources of banking customers. Meanwhile, the Bank’s valuable customers are one of the best resources to make profit for banks. Several different models are introduced for evaluation of profitability of the customers; but most of them are classical models and they are unable to evaluate the customers in complete and o...
متن کاملThe Application of Combined Fuzzy Clustering Model and Neural Networks to Measure Valuably of Bank Customers
Currently, acquisition of resources in banks is subject to attraction of the resources of banking customers. Meanwhile, the Bank’s valuable customers are one of the best resources to make profit for banks. Several different models are introduced for evaluation of profitability of the customers; but most of them are classical models and they are unable to evaluate the customers in complete and o...
متن کاملHigh-Dimensional Unsupervised Active Learning Method
In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...
متن کاملImproved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring
In data mining, clustering is one of the important issues for separation and classification with groups like unsupervised data. In this paper, an attempt has been made to improve and optimize the application of clustering heuristic methods such as Genetic, PSO algorithm, Artificial bee colony algorithm, Harmony Search algorithm and Differential Evolution on the unlabeled data of an Iranian bank...
متن کامل