Clustering Patients with Tensor Decomposition
نویسندگان
چکیده
In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records. We present a robust and efficient heuristic to face this problem using tensor decomposition. We present the reasons why this approach is preferable for tasks such as clustering patient records, to more commonly used distance-based methods. We run the algorithm on two datasets of healthcare records, obtaining clinically meaningful results.
منابع مشابه
Hybrid Clustering of Multiple Information Sources via HOSVD
We present a hybrid clustering algorithm of multiple information sources via tensor decomposition, which can be regarded an extension of the spectral clustering based on modularity maximization. This hybrid clustering can be solved by the truncated higher-order singular value decomposition (HOSVD). Experimental results conducted on the synthetic data have demonstrated the effectiveness. keyword...
متن کاملMulti-Level Cluster Indicator Decompositions of Matrices and Tensors
A main challenging problem for many machine learning and data mining applications is that the amount of data and features are very large, so that low-rank approximations of original data are often required for efficient computation. We propose new multi-level clustering based low-rank matrix approximations which are comparable and even more compact than Singular Value Decomposition (SVD). We ut...
متن کاملMulti-View Subspace Clustering via Relaxed L1-Norm of Tensor Multi-Rank
In this paper, we address the multi-view subspace clustering problem. Our method utilize the circulant algebra for tensor, which is constructed by stacking the subspace representation matrices of different views and then shifting, to explore the high order correlations underlying multi-view data. By introducing a recently proposed tensor factorization, namely tensor-Singular Value Decomposition...
متن کاملA simple form of MT impedance tensor analysis to simplify its decomposition to remove the effects of near surface small-scale 3-D conductivity structures
Magnetotelluric (MT) is a natural electromagnetic (EM) technique which is used for geothermal, petroleum, geotechnical, groundwater and mineral exploration. MT is also routinely used for mapping of deep subsurface structures. In this method, the measured regional complex impedance tensor (Z) is substantially distorted by any topographical feature or small-scale near-surface, three-dimensional (...
متن کاملGraph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members
Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...
متن کامل