scholarly journals A soft subspace clustering algorithm with log-transformed distances

2015 ◽  
Vol 1 (1) ◽  
pp. 93-109 ◽  
Author(s):  
Guojun Gan ◽  
Kun Chen
Keyword(s):  
Clustering Algorithm ◽  
Subspace Clustering

scholarly journals A Nonconvex Implementation of Sparse Subspace Clustering: Algorithm and Convergence Analysis

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 54741-54750 ◽  
Author(s):  
Xiaoge Deng ◽  
Tao Sun ◽  
Peibing Du ◽  
Dongsheng Li
Keyword(s):  
Convergence Analysis ◽  
Clustering Algorithm ◽  
Subspace Clustering ◽  
Sparse Subspace Clustering

Improved Object Recognition with Decision Trees Using Subspace Clustering

2016 ◽  
Vol 20 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Billy Peralta ◽  
◽  
Luis Alberto Caro
Keyword(s):  
Object Recognition ◽  
Decision Trees ◽  
Clustering Algorithm ◽  
Comprehensive Evaluation ◽  
Recognition Performance ◽  
Clustering Algorithms ◽  
Subspace Clustering ◽  
Visual Words ◽  
Ensemble Techniques ◽  
Standard Object

Generic object recognition algorithms usually require complex classificationmodels because of intrinsic difficulties arising from problems such as changes in pose, lighting conditions, or partial occlusions. Decision trees present an inexpensive alternative for classification tasks and offer the advantage of being simple to understand. On the other hand, a common scheme for object recognition is given by the appearances of visual words, also known as the bag-of-words method. Although multiple co-occurrences of visual words are more informative regarding visual classes, a comprehensive evaluation of such combinations is unfeasible because it would result in a combinatorial explosion. In this paper, we propose to obtain the multiple co-occurrences of visual words using a variant of the CLIQUE subspace-clustering algorithm for improving the object recognition performance of simple decision trees. Experiments on standard object datasets show that our method improves the accuracy of the classification of generic objects in comparison to traditional decision tree techniques that are similar, in terms of accuracy, to ensemble techniques. In future we plan to evaluate other variants of decision trees, and apply other subspace-clustering algorithms.

Applications of a new subspace clustering algorithm (COSA) in medical systems biology

Metabolomics ◽  
2007 ◽  
Vol 3 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Doris Damian ◽  
Matej Orešič ◽  
Elwin Verheij ◽  
Jacqueline Meulman ◽  
Jerome Friedman ◽  
...  
Keyword(s):  
Systems Biology ◽  
Clustering Algorithm ◽  
Subspace Clustering ◽  
Medical Systems

Active learning for improving a soft subspace clustering algorithm

2015 ◽  
Vol 46 ◽  
pp. 196-208 ◽  
Author(s):  
Amel Boulemnadjel ◽  
Fella Hachouf ◽  
Amel Hebboul ◽  
Khalifa Djemal
Keyword(s):  
Active Learning ◽  
Clustering Algorithm ◽  
Subspace Clustering
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