Andrew Lensen

PhD Student School of Engineering and Computer Science

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Thesis Info

Research Interests: Evolutionary Computation, Feature Selection, Feature Construction, Clustering, Computer Vision, Neural Networks
Thesis Title: An Evolutionary Feature Reduction Approach to Clustering
Supervisor: Prof Mengjie Zhang and Dr Bing Xue

 

Drawbacks of k-means: http://stats.stackexchange.com/questions/133656/how-to-understand-the-drawbacks-of-k-means

Clustering Datasets

A few useful clustering dataset links:
UCI -- classification datasets that can be used for clustering by ignoring the class label. The class label is useful for evaluating the accuracy of the clusterer in recreating the known classification (though care should be taken -- producing clusters that do not directly match the known classes doesn't mean the clusters are bad...): https://archive.ics.uci.edu/ml/datasets.html

Handl et al. -- hyper-spherical synthetic datasets with high dimensionality and number of clusters (up to 100 and 40 respectively): http://personalpages.manchester.ac.uk/mbs/julia.handl/generators.html

A collection of other datasets, including some interesting non-hyper-spherical (NHS) ones: https://cs.joensuu.fi/sipu/datasets/

Publications

PDFs for the papers below can be found at http://andrewlensen.com/publications.html for academic/educational purposes.
The best place to get bibtex citations is usually here.
  1. Andrew Lensen, Bing Xue, and Mengjie Zhang. "New Representations in Genetic Programming for Feature Construction in k-means Clustering". Proceedings of The 11th International Conference on Simulated Evolution and Learning (SEAL2017) . 2017. (To Appear).
  2. Andrew Lensen, Bing Xue, and Mengjie Zhang. "GPGC: Genetic Programming for Automatic Clustering using a Flexible Non-Hyper-Spherical Graph-Based Approach". Proceedings of The Genetic and Evolutionary Computation Conference (GECCO 2017). pages 449-456. ACM, 2017.
  3. Andrew Lensen, Bing Xue, and Mengjie Zhang. "Improving k-means Clustering with Genetic Programming for Feature Construction". Proceedings of The Genetic and Evolutionary Computation Conference (GECCO 2017) Companion. pages 237-238. ACM, 2017.
  4. Andrew Lensen, Bing Xue, and Mengjie Zhang. "Using Particle Swarm Optimisation and the Silhouette Metric to Estimate the Number of Clusters, Select Features, and Perform Clustering". Proceedings of the 20th European Conference on the Applications of Evolutionary Computation (EvoApplications 2017). pages 538-554. Lecture Notes in Computer Science, volume 10199. Springer, 2017.
  5. Andrew Lensen, Bing Xue, and Mengjie Zhang. "Particle Swarm Optimisation Representations for Simultaneous Clustering and Feature Selection". Proceedings of the Symposium Series on Computational Intelligence (SSCI 2016). pages 1-8. IEEE Press, 2016.
  6. Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, and Bing Xue. "Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data". Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016). pages 51-67. Lecture Notes in Computer Science, volume 9594. Springer, 2016.
  7. Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, and Bing Xue. "A Hybrid Genetic Programming Approach to Feature Detection and Image Classification". Proceedings of the 30th International Conference on Image and Vision Computing New Zealand (IVCNZ 2015). pages 1-6. IEEE Press, 2015.
  8. Andrew Lensen, Harith Al-Sahaf, Mengjie Zhang, and Brijesh Verma. "Genetic Programming for Algae Detection in River Images". Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2015), pages 2468-2475. IEEE Press, 2015.

Main.GraduateForm edit

ResearchAreas Evolutionary Computation, Feature Selection, Feature Construction, Clustering, Computer Vision, Neural Networks
ThesisTitle An Evolutionary Feature Reduction Approach to Clustering
Supervisor Prof Mengjie Zhang and Dr Bing Xue
Qualifications BSc (Hons 1st Class) Computer Science
Photo I allow my photo to be used for the photo board
Topic attachments
I Attachment Action Size Date Who Comment
An Evolutionary Feature Reduction Approach to Clustering.pptxpptx An Evolutionary Feature Reduction Approach to Clustering.pptx manage 1 MB 27 Mar 2017 - 12:55 Main.lensenandr  
EvoStar 2017 Lensen.pptxpptx EvoStar 2017 Lensen.pptx manage 1 MB 16 Feb 2017 - 17:49 Main.lensenandr  
GECCO 2017 Lensen.pptxpptx GECCO 2017 Lensen.pptx manage 1 MB 23 Jun 2017 - 14:58 Main.lensenandr  
GECCOPoster2017.pdfpdf GECCOPoster2017.pdf manage 657 K 09 Jun 2017 - 12:28 Main.lensenandr  
SEAL 2017 Lensen.pptxpptx SEAL 2017 Lensen.pptx manage 1 MB 20 Oct 2017 - 14:59 Main.lensenandr  
SSCI_2016_Lensen.pptxpptx SSCI_2016_Lensen.pptx manage 1 MB 18 Nov 2016 - 14:46 Main.lensenandr  
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Topic revision: 20 Oct 2017, lensenandr