Algorithms for clustering data
Algorithms for clustering data
An iterative linear programming solution to the Euclidean regression model
Computers and Operations Research
Mathematical algorithms for linear regression
Mathematical algorithms for linear regression
Fundamentals of Artificial Neural Networks
Fundamentals of Artificial Neural Networks
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Introduction to mathematical techniques in pattern recognition
Introduction to mathematical techniques in pattern recognition
The MIN PFS problem and piecewise linear model estimation
Discrete Applied Mathematics - Special issue: Third ALIO-EURO meeting on applied combinatorial optimization
A divisive information theoretic feature clustering algorithm for text classification
The Journal of Machine Learning Research
Computing smallest singular triplets with implicitly restarted Lanczos bidiagonalization
Applied Numerical Mathematics - Numerical algorithms, parallelism and applications
Local Optimization Method with Global Multidimensional Search
Journal of Global Optimization
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the use of sparse signal decomposition in the analysis of multi-channel surface electromyograms
Signal Processing - Sparse approximations in signal and image processing
Robust sparse component analysis based on a generalized Hough transform
EURASIP Journal on Applied Signal Processing
A bilinear algorithm for sparse representations
Computational Optimization and Applications
An Efficient K-Hyperplane Clustering Algorithm and Its Application to Sparse Component Analysis
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Spectral Curvature Clustering (SCC)
International Journal of Computer Vision
AGRID: an efficient algorithm for clustering large high-dimensional datasets
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
A greedy approach to identification of piecewise affine models
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
Identifiability conditions and subspace clustering in sparse BSS
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Learning sparse representation using iterative subspace identification
IEEE Transactions on Signal Processing
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Fuzzy hyper-prototype clustering
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
A k-plane clustering algorithm for identification of hybrid systems
ACMOS'06 Proceedings of the 8th WSEAS international conference on Automatic control, modeling & simulation
Data mining algorithms and techniques research in CRM systems
MAMECTIS/NOLASC/CONTROL/WAMUS'11 Proceedings of the 13th WSEAS international conference on mathematical methods, computational techniques and intelligent systems, and 10th WSEAS international conference on non-linear analysis, non-linear systems and chaos, and 7th WSEAS international conference on dynamical systems and control, and 11th WSEAS international conference on Wavelet analysis and multirate systems: recent researches in computational techniques, non-linear systems and control
An efficient algorithm for maximal margin clustering
Journal of Global Optimization
A spatially constrained fuzzy hyper-prototype clustering algorithm
Pattern Recognition
Partitive clustering (K-means family)
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Hybrid Linear Modeling via Local Best-Fit Flats
International Journal of Computer Vision
Robust and efficient subspace segmentation via least squares regression
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Column Generation for the Minimum Hyperplanes Clustering Problem
INFORMS Journal on Computing
Research on hotspot discovery in internet public opinions based on improved K-means
Computational Intelligence and Neuroscience
Subspace clustering of high-dimensional data: a predictive approach
Data Mining and Knowledge Discovery
FHC: The fuzzy hyper-prototype clustering algorithm
International Journal of Knowledge-based and Intelligent Engineering Systems - Intelligent Information Processing: Techniques and Applications
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A finite new algorithm is proposed for clustering m given points in n-dimensional real space into k clusters by generating k planes that constitute a local solution to the nonconvex problem of minimizing the sum of squares of the 2-norm distances between each point and a nearest plane. The key to the algorithm lies in a formulation that generates a plane in n-dimensional space that minimizes the sum of the squares of the 2-norm distances to each of m1 given points in the space. The plane is generated by an eigenvector corresponding to a smallest eigenvalue of an n × n simple matrix derived from the m1 points. The algorithm was tested on the publicly available Wisconsin Breast Prognosis Cancer database to generate well separated patient survival curves. In contrast, the k-mean algorithm did not generate such well-separated survival curves.