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Support Vector Machines with Manifold Learning and Probabilistic Space Projection for Tourist Expenditure Analysis

Xin Xu, Rob Law, Tao Wu
2009 International Journal of Computational Intelligence Systems  
In this paper, a novel method using SVMbased classification with two nonlinear feature projection techniques is proposed for tourism data analysis.  ...  By making use of ISOMAP, part of the noisy data can be identified and the classification accuracy of SVMs can be improved by appropriately discarding the noisy training data.  ...  Acknowledgements The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 4631/06H).  ... 
doi:10.1080/18756891.2009.9727636 fatcat:7nobrzfrlbf4xok7aoqanjm2bi

Support Vector Machines with Manifold Learning and Probabilistic Space Projection for Tourist Expenditure Analysis

Xin Xu, Rob Law, Tao Wu
2009 International Journal of Computational Intelligence Systems  
In this paper, a novel method using SVMbased classification with two nonlinear feature projection techniques is proposed for tourism data analysis.  ...  By making use of ISOMAP, part of the noisy data can be identified and the classification accuracy of SVMs can be improved by appropriately discarding the noisy training data.  ...  Acknowledgements The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 4631/06H).  ... 
doi:10.2991/jnmp.2009.2.1.3 fatcat:h5h64gjyb5bv3mgtz2rdaopk4q

Research on the Machine Learning Algorithms on Heart Condition Predictions

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
By increasing the use of machine learning algorithms, the accuracy of each algorithm is calculated and the quality and value of the health services increases efficiency.  ...  Now-a-days Health care monitoring widely uses Internet of Things (IoT) and big data which is further integrated into wearable bio sensors.  ...  Then the accuracy of the model will be changed appropriately. 1) PCA (Principal Component analysis): Primary Component Analysis (PCA) is a statistical procedure using an orthogonal transformation to  ... 
doi:10.35940/ijitee.f1279.0486s419 fatcat:63zoqgynqvdmzebbpnmub3pbtm

Some evidence on forecasting time-series with support vector machines

J V Hansen, J B McDonald, R D Nelson
2006 Journal of the Operational Research Society  
The principal advantage of this four-parameter family of distributions is that it permits a wide varjety of tail thickness and skewness combinations.  ...  /ntroductory Business and Economic Forecasting. South-Western Publishing: Cincinnati, OH. Scholkopf B and Smola A (2002). Learning with Kernels.  ... 
doi:10.1057/palgrave.jors.2602073 fatcat:fofrkb6vbbcmjlv765e2cnlplq

A Literature Survey on the Importance of Intrusion Detection System for Wireless Networks

D. Selvamani, V. Selvi
2018 Asian Journal of Computer Science and Technology  
With the advent of the internet, security became a major concern and the history of security allows a better understanding of the emergence of security technology.  ...  In order to understand the research being performed today, background knowledge of the importance of security, types of attacks in the networks.  ...  Fangjun Kuang [10] proposed a novel support vector machine (SVM) model combining kernel principal component analysis (KPCA) with genetic algorithm (GA) is proposed for intrusion detection.  ... 
doi:10.51983/ajcst-2018.7.3.1905 fatcat:v63hfbqvybbaxj2nvnuybcgaza

Development of a Representative EV Urban Driving Cycle Based on a k-Means and SVM Hybrid Clustering Algorithm

Xuan Zhao, Qiang Yu, Jian Ma, Yan Wu, Man Yu, Yiming Ye
2018 Journal of Advanced Transportation  
Principal component analysis (PCA) is used to reduce the dimensionality of the characteristic parameters.  ...  The driving segments are classified using a hybrid k-means and support vector machine (SVM) clustering algorithm.  ...  The "Driving Cycle" file records the speed-time data of driving cycle based on k-means and SVM proposed in this paper. (Supplementary Materials)  ... 
doi:10.1155/2018/1890753 fatcat:7taqcraf7fcejdzzzrwrx6t5x4

IoT Information Status Using Data Fusion and Feature Extraction Method

S. S. Saranya, N. Sabiyath Fatima
2022 Computers Materials & Continua  
Improved Principal Component Analysis is deployed for feature extraction along with dimension reduction.  ...  The Internet of Things (IoT) role is instrumental in the technological advancement of the healthcare industry.  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmc.2022.019621 fatcat:hkd3hw33lbcvphsoegi33xcgnm

Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

Tao Wu, Huiqing Shen, Jianxin Qin, Longgang Xiang
2021 Sustainability  
the classifier classification.  ...  the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using  ...  Applications with Noise PCA Principal Component Analysis LDA Linear Discriminant Analysis GPS Global Position System SVM Support Vector Machine POI Point of Interest MCC Mobility Context Cube  ... 
doi:10.3390/su13020690 fatcat:hyoj4urf2nc25ffjg34sj5hp5a

Predictive Data Mining Techniques for Fault Diagnosis of Electric Equipment: A Review

Contreras-Valdes, Amezquita-Sanchez, Granados-Lieberman, Valtierra-Rodriguez
2020 Applied Sciences  
through the analysis and discovery of knowledge.  ...  Starting from the year 2000 to the present, a revision of the methods used in the tasks of classification and regression for the diagnosis of electric equipment is carried out.  ...  classifiers such as PNN, k-Nearest Neighbor (kNN), or principal components analysis.  ... 
doi:10.3390/app10030950 fatcat:bgp74acuvjd6fmzffyvkrbks2m

Spectral Clustering and Its Application in Machine Failure Prognosis [chapter]

Weihua Li, Yan Chen, Wen Liu, Jay Lee
2012 New Frontiers in Graph Theory  
), and Open Research Foundation of State Key Laboratory of Digital Manufacturing Equipment and Technology (DMETKF2009010).  ...  The authors would also like to thank Intelligent Maintenance System center in University of Cincinnati and its industry collabrator TechSolve Inc. for the investigation of feed axes system.  ...  Harkat et.al(2007) applied non-linear principal component analysis in sensor fault detection and isolation.  ... 
doi:10.5772/35970 fatcat:46woaljjbbgptja55qolfi4ycq

Differentiation Between Organic and Non-Organic Apples Using Diffraction Grating and Image Processing—A Cost-Effective Approach

Nanfeng Jiang, Weiran Song, Hui Wang, Gongde Guo, Yuanyuan Liu
2018 Sensors  
A popular approach to food authentication is based on spectroscopy, which has been widely used for identifying and quantifying the chemical components of an object.  ...  This sensor system consists of simple components (the hardware costs less than 3 US dollars on top of a smartphone) which are consumer-friendly and do not require expert knowledge to operate.  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/s18061667 pmid:29789501 pmcid:PMC6021810 fatcat:3m6cy5hu2jh2bocdqarl7pjgv4

Prediction and Risk Assessment Models for Subarachnoid Hemorrhage: A Systematic Review on Case Studies

Jewel Sengupta, Robertas Alzbutas, B. D. Parameshachari
2022 BioMed Research International  
The clinical factors with computed tomography (CT), magnetic resonance image (MRI), and electroencephalography (EEG) data were used to evaluate the performance of the developed method.  ...  In this paper, various methods such as statistical analysis, logistic regression, machine learning, and deep learning methods were used in the prediction and detection of SAH which are reviewed.  ...  This project has received funding from the European Regional Development Fund (project no. 01.2.2-LMT-K-718-03-0091) under grant agreement with the Research Council of Lithuania (LMTLT).  ... 
doi:10.1155/2022/5416726 pmid:35111845 pmcid:PMC8802084 fatcat:epo7dqt3hfccpfw53mbezuxe3e

Ultra-Wideband Radar-Based Activity Recognition Using Deep Learning

Farzan M. Noori, Md Zia Uddin, Jim Torressen
2021 IEEE Access  
As a UWB sensor collects many data points in a single frame, enhanced discriminant analysis was used to reduce the dimensions of the features through application of principal component analysis to the  ...  This enables the strengthening of eldercare with regard to daily routines and the provision of personalised care to users.  ...  Herein, a nonlinear multiclass SVM with a sigmoid kernel was used. Sigmoid is used as it's a popular kernel.  ... 
doi:10.1109/access.2021.3117667 fatcat:gallkkhcejeh3lcdvy5fwrtknm

Sentiment Analysis: A Survey of Current Research and Techniques
english

Jeevanandam Jothees waran, Dr. S. Koteeswaran
2015 International Journal of Innovative Research in Computer and Communication Engineering  
This study ensures an overall survey about OM related to product reviews, and classification algorithms used for sentiment classification.  ...  Economic and marketing researches depend heavily on accurate method to predict sentiments of opinions extracted from internet and predict online customer's preferences.  ...  Feature selection methods are,  Correlation based feature selector (CFS),  Information Gain,  Support Vector Machine (SVM),  Principal component analysis (PCA) 1.2 CLASSIFICATION METHODS IN OPINION  ... 
doi:10.15680/ijircce.2015.0305002 fatcat:gnt6bltl2bfvxnspyewmwlzqmu

Video Data Extraction and Processing for Investigation of Vehicles' Impact on the Asphalt Deformation Through the Prism of Computational Algorithms

Sabahudin Vrtagić, Edis Softić, Mirza Ponjavić, Željko Stević, Marko Subotić, Aditya Gmanjunath, Jasmin Kevric
2020 Traitement du signal  
classification using a combination of Histogram of Oriented Gradients (HOG) and Support Vector Machines (Linear SVM) has shown to be more appropriate as the original source data can be used for training  ...  From the video file sources, data regarding number of vehicles, speed, traveling direction, and time intervals for the region of interest will be collected.  ...  Associating the performance of NNs with SVMs, SVMs outclassed NNs using either principal component analysis (PCA) or Gabor entities.  ... 
doi:10.18280/ts.370603 fatcat:7p3j4inj4ng57lkx4qwx2doqqi
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