A method for outlier detection based on cluster analysis and visual expert criteria
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David Lizcano | Javier Soriano | Víctor Rampérez | David Lizcano | Juan A. Lara | J. Soriano | J. Lara | D. Lizcano | Víctor Rampérez
[1] Lara Torralbo,et al. Marco de Descubrimiento de Conocimiento para DatosEstructuralmente Complejos con Énfasis en el Análisis de Eventos en Series Temporales , 2011 .
[2] Dimitrios I. Fotiadis,et al. Automatic Seizure Detection Based on Time-Frequency Analysis and Artificial Neural Networks , 2007, Comput. Intell. Neurosci..
[3] Carlos Soares,et al. Outlier Detection using Clustering Methods: a data cleaning application , 2004 .
[4] Rajeev Rastogi,et al. Efficient algorithms for mining outliers from large data sets , 2000, SIGMOD 2000.
[5] Montserrat Lázaro,et al. Valor de la posturografía en ancianos con caídas de repetición , 2005 .
[6] Hassan Takabi,et al. Using EEG Signal to Analyze IS Decision Making Cognitive Processes , 2018 .
[7] Padhraic Smyth,et al. From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.
[8] Hiroki Takada,et al. Stabilometry to Evaluate Severity of Motion Sickness on Displays , 2018, Current Topics in Environmental Health and Preventive Medicine.
[9] F. Owen Black,et al. Postural Control in Four Classes of Vestibular Abnormalities1 , 1985 .
[10] Jeen-Shing Wang,et al. A Cluster Validity Measure With Outlier Detection for Support Vector Clustering , 2008, IEEE Trans. Syst. Man Cybern. Part B.
[11] Luís Torgo,et al. Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data , 2009, EPIA.
[12] Wang Jeen-Shing,et al. A Cluster Validity Measure With Outlier Detection for Support Vector Clustering , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[13] Luís Torgo,et al. Resource-Bounded Fraud Detection , 2007, EPIA Workshops.
[14] Shikha Agrawal,et al. Survey on Anomaly Detection using Data Mining Techniques , 2015, KES.
[15] Juan Alfonso Lara,et al. A general framework for time series data mining based on event analysis: Application to the medical domains of electroencephalography and stabilometry , 2014, J. Biomed. Informatics.
[16] Kenton R Kaufman,et al. Significant reduction in risk of falls and back pain in osteoporotic-kyphotic women through a Spinal Proprioceptive Extension Exercise Dynamic (SPEED) program. , 2005, Mayo Clinic proceedings.
[17] S. Scataglini. Posturography , 2019, DHM and Posturography.
[18] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.
[19] F. Chung,et al. The Assessment of Postural Stability After Ambulatory Anesthesia: A Comparison of Desflurane with Propofol , 2002 .
[20] Raymond T. Ng,et al. Finding Intensional Knowledge of Distance-Based Outliers , 1999, VLDB.
[21] Stefan Berchtold,et al. Efficient Biased Sampling for Approximate Clustering and Outlier Detection in Large Data Sets , 2003, IEEE Trans. Knowl. Data Eng..
[22] Maurizio Filippone,et al. A comparative evaluation of outlier detection algorithms: Experiments and analyses , 2018, Pattern Recognit..
[23] Doo-Hwan Bae,et al. An Approach to Outlier Detection of Software Measurement Data using the K-means Clustering Method , 2007, ESEM 2007.
[24] Dimitrios Gunopulos,et al. Automatic subspace clustering of high dimensional data for data mining applications , 1998, SIGMOD '98.
[25] Ian T. Jolliffe,et al. Principal Component Analysis , 1986, Springer Series in Statistics.
[26] Tomoe Yoshida,et al. Japanese standard for clinical stabilometry assessment: Current status and future directions. , 2018, Auris, nasus, larynx.
[27] B Kovalerchuk,et al. Consistent knowledge discovery in medical diagnosis. , 2000, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.
[28] Philip S. Yu,et al. Outlier detection for high dimensional data , 2001, SIGMOD '01.
[29] Abdulhamit Subasi,et al. A decision support system for automated identification of sleep stages from single-channel EEG signals , 2017, Knowl. Based Syst..
[30] William Perrizo,et al. A vertical outlier detection algorithm with clusters as by-product , 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.
[31] Ashish Ghosh,et al. Integration of deep feature extraction and ensemble learning for outlier detection , 2019, Pattern Recognit..
[32] Raymond T. Ng,et al. Algorithms for Mining Distance-Based Outliers in Large Datasets , 1998, VLDB.
[33] Clara Pizzuti,et al. Distance-based detection and prediction of outliers , 2006, IEEE Transactions on Knowledge and Data Engineering.
[34] Peng Yang,et al. A Spectral Clustering Algorithm for Outlier Detection , 2008, 2008 International Seminar on Future Information Technology and Management Engineering.
[35] Gentiane Haesbroeck,et al. Comparison of local outlier detection techniques in spatial multivariate data , 2017, Data Mining and Knowledge Discovery.
[36] Warren S. Sarle,et al. Cubic Clustering Criterion , 1983 .
[37] Shian-Shyong Tseng,et al. Two-phase clustering process for outliers detection , 2001, Pattern Recognit. Lett..
[38] Ada Wai-Chee Fu,et al. Efficient time series matching by wavelets , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).
[39] E Donchin,et al. Brain-computer interface technology: a review of the first international meeting. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[40] Hans-Peter Kriegel,et al. LOF: identifying density-based local outliers , 2000, SIGMOD 2000.
[41] A. Ben Hamza,et al. Cluster pca for outliers detection in high-dimensional data , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.
[42] J. M. Ronda,et al. Asociación entre síntomas clínicos y resultados de la posturografía computarizada dinámica , 2002 .
[43] Richard J. Povinelli,et al. Time series data mining: identifying temporal patterns for characterization and prediction of time series events , 1999 .
[44] Christos Faloutsos,et al. Efficient Similarity Search In Sequence Databases , 1993, FODO.
[45] T. Sørensen,et al. A method of establishing group of equal amplitude in plant sociobiology based on similarity of species content and its application to analyses of the vegetation on Danish commons , 1948 .
[46] F O Black,et al. Vestibulo-spinal control differs in patients with reduced versus distorted vestibular function. , 1984, Acta oto-laryngologica. Supplementum.
[47] J. Eisman,et al. Identification of High‐Risk Individuals for Hip Fracture: A 14‐Year Prospective Study , 2005, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.
[48] R. Barry,et al. A review of electrophysiology in attention-deficit/hyperactivity disorder: I. Qualitative and quantitative electroencephalography , 2003, Clinical Neurophysiology.
[49] K Lehnertz,et al. Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.
[50] Daniel T. Larose,et al. Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .
[51] Hui Xiong,et al. Manhattan Distance , 2008, Encyclopedia of GIS.
[52] Eduardo Martín Sanz,et al. Vértigo paroxístico benigno infantil: categorización y comparación con el vértigo posicional paroxístico benigno del adulto , 2007 .
[53] Victoria J. Hodge,et al. A Survey of Outlier Detection Methodologies , 2004, Artificial Intelligence Review.