Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing

Journal article


Hajderanj, L., Chen, D., Grisan, E. and Dudley-McEvoy, S (2020). Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing. IEEE Access.
AuthorsHajderanj, L., Chen, D., Grisan, E. and Dudley-McEvoy, S
Abstract

In recent years, the huge expansion of digital technologies has vastly increased the volume of data to be explored, such that reducing the dimensionality of data is an essential step in data exploration. The integrity of a dimensionality reduction technique relates to the goodness of maintaining the data structure. Dimensionality reduction techniques such as Principal Component Analyses (PCA) and Multidimensional
Scaling (MDS) globally preserve the distance ranking at the expense of neglecting small-distance preservation. Conversely, the structure capturing of some other methods such as Isomap, Locally Linear Embedding (LLE), Laplacian Eigenmaps t-Stochastic Neighbour Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP), and TriMap rely on the number of neighbours considered. This paper presents a dimensionality reduction technique, Same Degree Distribution (SDD) that does not rely on the number of neighbours, thanks to using degree-distributions in both high and low dimensional spaces. Degree-distribution is similar to Student-t distribution and is less expensive than Gaussian distribution. As such, it enables better global data preservation in less computational time. Moreover, to improve the data structure capturing, SDD has been extended to Multi-SDDs (MSDD), which employs various degree distributions on top of SDD. The proposed approach and its extension demonstrated a greater performance compared with eight other benchmark methods, tested in several popular synthetics and real datasets such as Iris, Breast Cancer, Swiss Roll, MNIST, and Make Blob evaluated by the co-ranking matrix and Kendall’s Tau coefficient. For further work, we aim to approximate the number of distributions and their degrees in relation to the given dataset. Reducing the computational complexity is another objective for further work.

Keywordsdimensionality reduction; global structure; local structure; visualization; structure capturing
Year2020
JournalIEEE Access
PublisherInstitute of Electrical and Electronics Engineers
ISSN2169-3536
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Accepted05 Nov 2020
Deposited05 Nov 2020
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Superpixel-based classification of gastric chromoendoscopy images
Boschetto, D and Grisan, E (2017). Superpixel-based classification of gastric chromoendoscopy images. SPIE Medical Imaging. Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2254187
Boosted learned kernels for data-driven vesselness measure
Grisan, E (2017). Boosted learned kernels for data-driven vesselness measure. Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101370Z (2017). Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2250370
Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling
Palombit, A, Castellaro, M, Calabrese, M, Romualdi, C, Pizzini, FB, Montemezzi, S, Grisan, E and Bertoldo, A (2017). Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 18 - 21 Apr 2017 pp. 792-795 https://doi.org/10.1109/ISBI.2017.7950637
From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis
Grisan, E, Rizzo, G, Tonietto, M, Coran, A, Raffeiner, B, Scanu, A, Martini, V, Stramare, R and Fiocco, U (2017). From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 17 - 21 Apr 2017 IEEE. pp. 899-902 https://doi.org/10.1109/ISBI.2017.7950661
Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α
Raffeiner, B, Grisan, E, Botsios, C, Stramare, R, Rizzo, G, Bernardi, L, Punzi, L, Ometto, F and Doria, A (2017). Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α. Rheumatology (United Kingdom). 56, pp. 1320-1325. https://doi.org/10.1093/rheumatology/kex084
Bayesian Quantification of Contrast-Enhanced Ultrasound Images with Adaptive Inclusion of an Irreversible Component
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Bayesian Quantification of Contrast-Enhanced Ultrasound Images with Adaptive Inclusion of an Irreversible Component. IEEE Transactions on Medical Imaging. 36, pp. 1027-1036. https://doi.org/https://www.doi.org/10.1109/TMI.2016.2637698
Tcf7l2 plays pleiotropic roles in the control of glucose homeostasis, pancreas morphology, vascularization and regeneration
Facchinello, N, Tarifeño-Saldivia, E, Grisan, E, Schiavone, M, Peron, M, Mongera, A, Ek, O, Schmitner, N, Meyer, D, Peers, B, Tiso, N and Argenton, F (2017). Tcf7l2 plays pleiotropic roles in the control of glucose homeostasis, pancreas morphology, vascularization and regeneration. Scientific Reports. 7. https://doi.org/https://www.doi.org/10.1038/s41598-017-09867-x
Growth abnormalities of fetuses and infants
Cosmi, E, Grisan, E, Fanos, V, Rizzo, G, Sivanandam, S and Visentin, S (2017). Growth abnormalities of fetuses and infants. BioMed Research International. 2017. https://doi.org/https://www.doi.org/10.1155/2017/3191308
A possible new approach in the prediction of late gestational hypertension: The role of the fetal aortic intima-media thickness
Visentin, S, Londero, AP, Camerin, M, Grisan, E and Cosmi, E (2017). A possible new approach in the prediction of late gestational hypertension: The role of the fetal aortic intima-media thickness. Medicine (United States). 96. https://doi.org/https://www.doi.org/10.1097/MD.0000000000005515
Occupancy Based Household Energy Disaggregation using Ultra Wideband Radar and Electrical Signature Profiles
Brown, R, Ghavami, N, Siddiqui, H, Adjrad, M, Ghavami, M and Dudley, S (2017). Occupancy Based Household Energy Disaggregation using Ultra Wideband Radar and Electrical Signature Profiles. Energy and Buildings. 141, pp. 134-141.
HACH: Heuristic Algorithm for Clustering Hierarchy Protocol in Wireless Sensor Network
Dudley, S, Turkey, M and Oladimeji, MO (2017). HACH: Heuristic Algorithm for Clustering Hierarchy Protocol in Wireless Sensor Network. Applied Soft Computing.
Experimental Validation of a Thirteen Level H-Bridge Photovoltaic Inverter Configuration
Dudley, S, Loukriz, A and Quinlan, T (2017). Experimental Validation of a Thirteen Level H-Bridge Photovoltaic Inverter Configuration. IEEE EEEIC17 and I&CPS Europe. Milan, Italy 06 - 09 Jun 2017 Institute of Electrical and Electronics Engineers (IEEE).
Unsupervised Learning Techniques for HVAC Terminal Unit Behaviour Analysis
Dey, M, Gupta, M, Turkey, M and Dudley, S (2017). Unsupervised Learning Techniques for HVAC Terminal Unit Behaviour Analysis. IEEE International Conference on Smart City Innovations. Fremont, California, USA 04 - 08 Aug 2017 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/UIC-ATC.2017.8397584
Learning Bayesian Network Parameters from a Small Data Set: A Further Constrained Qualitatively Maximum a Posteriori Method
Guo, Zhi-gao, Gao, Xiao-guang, Hao, Ren, Yang, Yu, Di, Ruo-hai and Chen, D (2017). Learning Bayesian Network Parameters from a Small Data Set: A Further Constrained Qualitatively Maximum a Posteriori Method. International Journal of Approximate Reasoning. 91 (Dec), pp. 22-35. https://doi.org/10.1016/j.ijar.2017.08.009
Feature Extraction and Labelling Large Data Sets Using Deep Learning
Chen, D (2017). Feature Extraction and Labelling Large Data Sets Using Deep Learning. RESEARCHER LINK: Smart Technology for Fighting Virus Epidemics & Bioinformatics. Recife, Pernambuco, Brazil 10 - 13 Sep 2017
UWB Localization Employing Supervised Learning Method
Rana, S., Dey, M., Siddiqui, H., Tiberi, G., Ghavami, M. and Dudley, S (2017). UWB Localization Employing Supervised Learning Method. IEEE International Conference on Ubiquitous Wireless Broadband 2017. Salamanca, Spain 12 - 15 Sep 2017 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICUWB.2017.8250971
Prediction of Breast Cancer Survivability using Ensemble Algorithms
Adegoke, V, Chen, D, Banissi, E and Barikzai, S (2017). Prediction of Breast Cancer Survivability using Ensemble Algorithms. International Conference on Smart System and Technologies 2017 (SST 2017),. Osijek, Croatia 18 - 20 Oct 2017
A PID Inspired Feature Extraction for HVAC Terminal Units
Dey, M, Gupta, M, Rana, S., Turkey, M and Dudley, S (2017). A PID Inspired Feature Extraction for HVAC Terminal Units. IEEE Conference on Technologies for Sustainability (SusTech 2017). Phoenix, Arizona, USA 12 - 14 Nov 2017 Institute of Electrical and Electronics Engineers (IEEE).
Predictive Ensemble Modelling: An Experimental Comparison of Boosting Implementation Methods
Adegoke, V, Chen, D, Barikzai, S and Banissi, E (2017). Predictive Ensemble Modelling: An Experimental Comparison of Boosting Implementation Methods. 2017 European Modelling Symposium (EMS). Manchester 20 - 21 Nov 2017
Automatic classification of small bowel mucosa alterations in celiac disease for confocal laser endomicroscopy
Boschetto, D, Di Claudio, G, Mirzaei, H, Leong, R and Grisan, E (2016). Automatic classification of small bowel mucosa alterations in celiac disease for confocal laser endomicroscopy. Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. San Diego, United States 27 Feb - 03 Mar 2016 SPIE. https://doi.org/10.1117/12.2217183
Automatic classification of endoscopic images for premalignant conditions of the esophagus
Boschetto, D, Gambaretto, G and Grisan, E (2016). Automatic classification of endoscopic images for premalignant conditions of the esophagus. Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. San Diego, United States 27 Feb - 03 Mar 2016 https://doi.org/10.1117/12.2216826
Superpixel-based automatic segmentation of villi in confocal endomicroscopy
Boschetto, D, Mirzaei, H, Leong, RWL and Grisan, E (2016). Superpixel-based automatic segmentation of villi in confocal endomicroscopy. 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). Las Vegas, NV, USA 24 - 27 Feb 2016 pp. 168-171 https://doi.org/10.1109/BHI.2016.7455861
Adaptive robust video broadcast via satellite
Altaf, M, Khan, FA, Khan, N, Ghanbari, M and Dudley, S (2016). Adaptive robust video broadcast via satellite. Multimedia Tools and Applications. 76 (6), pp. 7785-7801. https://doi.org/10.1007/s11042-016-3426-y
Making Better Use of Big Data
Chen, D (2016). Making Better Use of Big Data. LSBU Enterprise Count Event, March 2016. London Southbank University 18 - 18 Mar 2016 London South Bank University.
Experimental Realization of a Single-Phase Five Level Inverter for PV Applications
Loukriz, A, Dudley, S, Quinlan, T and Walker, S (2016). Experimental Realization of a Single-Phase Five Level Inverter for PV Applications. IEEE Workshop on Control and Modeling for Power Electronics (COMPEL) 2016. Trondheim, Norway 27 - 30 Jun 2016 Institute of Electrical and Electronics Engineers (IEEE).
Big Data Analytics In The Public Sector: A Case Study Of NEET Analysis For The London Boroughs
Chen, D, Asaolu, B and Qin, C (2016). Big Data Analytics In The Public Sector: A Case Study Of NEET Analysis For The London Boroughs. International Conference on Big Data Analytics, Data Mining and Computational Intelligence. Funchal, Madeira, Portugal 02 - 04 Jul 2016
Huygens Principle based UWB Microwave Imaging Method for Skin Cancer Detection
Ghavami, N, Tiberi, G, Ghavami, M, Dudley, S and Lane, ME (2016). Huygens Principle based UWB Microwave Imaging Method for Skin Cancer Detection. 10th IEEE/IET International Symposium on Communication Systems, Networks and Digital Signal Processing. Prague, Czech Republic 20 - 22 Jul 2016 Institute of Electrical and Electronics Engineers (IEEE).
Iterated Local Search Algorithm for Clustering Wireless Sensor Networks.
Dudley, S, Oladimeji, MO and Turkey, M (2016). Iterated Local Search Algorithm for Clustering Wireless Sensor Networks. 2016 IEEE Congress on Evolutionary Computation (CEC). Vancouver, Canada 24 - 29 Jul 2016 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CEC.2016.7744200
Development of a Wall Climbing Robotic Ground Penetrating Radar System for Inspection of Vertical Concrete Structures
Sattar, TP, Howlader, MOF and Dudley, S (2016). Development of a Wall Climbing Robotic Ground Penetrating Radar System for Inspection of Vertical Concrete Structures. International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering. 10 (8), pp. 1346-1352.
A heuristic crossover enhanced evolutionary algorithm for clustering wireless sensor network
Oladimeji, MO, Turkey, M and Dudley, S (2016). A heuristic crossover enhanced evolutionary algorithm for clustering wireless sensor network. EvoApplications Evostar 2016. Porto, Portugal 30 Mar - 01 Apr 2016 https://doi.org/10.1007/978-3-319-31204-0_17
On Distributed Deep Network for Processing Large-Scale Sets of Complex Data
Qin, C, Gao, X and Chen, D (2016). On Distributed Deep Network for Processing Large-Scale Sets of Complex Data. 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). Hangzhou, China. 27 - 28 Aug 2016 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IHMSC.2016.55
On Distributed Deep Network for Processing Large-Scale Sets of Complex Data
Chen, D (2016). On Distributed Deep Network for Processing Large-Scale Sets of Complex Data. 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). Hangzhou, China 27 - 28 Aug 2016
A novel single-phase thirteen level inverter for photovoltaic application
Loukriz, A, Dudley, S, Messalti, S, Quinlan, T, Loukriz, A and Walker, S (2016). A novel single-phase thirteen level inverter for photovoltaic application. 8th International Conference on Modelling, Identification and Control (ICMIC-2016). Algiers, Algeria- November 15-17, 2016 15 - 17 Nov 2016 Institute of Electrical and Electronics Engineers (IEEE). pp. 532-537 https://doi.org/10.1109/ICMIC.2016.7804170
A Bayesian Approach to Learn Bayesian Networks Using Data and Constraints
Gao, X, Yu, Y, Zhi-gao, G and Chen, D (2016). A Bayesian Approach to Learn Bayesian Networks Using Data and Constraints. 23rd International Conference on Pattern Recognition (ICPR 2016). Cancún, México 04 - 08 Dec 2016 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICPR.2016.7900204
A semantic-enhanced trajectory visual analytics for digital forensic.
Liao, Z, Li, Y, Peng, Y, Zhao, Y, Zhou, F, Liao, Z, Dudley, S and Ghavami, M (2015). A semantic-enhanced trajectory visual analytics for digital forensic. Journal of Visualization. 18 (2), pp. 173 - 184. https://doi.org/10.1007/s12650-015-0276-z
Big Data Analytics System for Fact/Data-driven Decision Making
Chen, D (2015). Big Data Analytics System for Fact/Data-driven Decision Making. The Royal Statistical Society, Business and Industry Section. London, UK 18 Nov 2015 Royal Statistical Society .
A user-centric system architecture for residential energy consumption reduction
Vastardis, N, Adjrad, M, Buchanan, K, Liao, Z, Koch, C, Russo, R, Yang, K, Ghavami, M, Anderson, B and Dudley, S (2014). A user-centric system architecture for residential energy consumption reduction. IEEE Online Conference on Green Communications. Online 12 - 14 Nov 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 1-7 https://doi.org/10.1109/OnlineGreenCom.2014.7114423
Determining Key (Predictor) Modules for Early Identification of Students At-Risk
Chen, D and Elliott, G (2013). Determining Key (Predictor) Modules for Early Identification of Students At-Risk. International Conference on Advanced Information Engineering and Education Science (ICAIEES 2013). Beijing, China 19 - 20 Dec 2013 Atlantis Press. https://doi.org/10.2991/icaiees-13.2013.22
Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining
Chen, D (2012). Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining. Journal of Database Marketing and Customer Strategy Management. 19 (3), pp. 197-208. https://doi.org/10.1057/dbm.2012.17