Outlier analysis for microarray gene
Keywords:
Data Reduction, Outlier Analysis, Distance-based detection, Principle Component AnalysisAbstract
Pre-processing data is a critical component of data mining, as it comprises anomaly identification, outlier analysis, and dimensionality reduction utilising a distance-based technique. This research study demonstrates that in order to cope with scarcity difficulties in high dimensional spaces, computations should be limited to such data. A distance-based technique is seen more appropriate for the microarray-quality articulation of information delivered across many time zones.
Downloads
References
Bay, SD & Schwabacher, M 2003, ‘Mining Distance-Based Outliers in Near Linear Time with Randomization and a Simple Pruning Rule’, Proc. Ninth ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (KDD).
Yogeesh N. "Graphical Representation of Mathematical Equations Using Open Source Software." Journal of Advances and Scholarly Researches in Allied Education, vol. 16, no. 5, 2019, pp. 2204-2209 (6), www.ignited.in/p/304820.
Edwin M Knorr, Raymond T Ng & Vladimir Tucakov 2000, ‘Distance-based outliers: algorithms and applications’, The International Journal on Very Large Data Bases, vol. 8, no. 3-4, pp. 237-253.
Yogeesh N. "Mathematical Maxima Program to Show Corona (COVID-19) Disease Spread Over a Period." TUMBE Group of International Journals, vol. 3, no. 1, 2020, pp. 14-16.
Hawkins, S, He, H, Williams, GJ & Baxter, RA 2002, ‘Outlier detection using replicator neural networks’, In: Kambayashi, Y, Winiwarter, W, Arikawa, M. (eds.) DaWaK 2002. LNCS, Springer, Heidelberg, vol. 2454, pp. 170-180.
Girija D.K & M. S. Shashidhara, ‘Data mining techniques used for uterus fibroid diagnosis and prognosis’ In Kottayam, India, 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), INSPEC Accession Number: 13567035.
Girija D.K & M. S. Shashidhara, ‘Data mining approach for prediction of fibroid disease using neural networks’, Bangalore, India, 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA), INSPEC Accession Number: 14130830.
Ka Yee Yeung and Ruzzo W.L. (2000), ‘An Empirical Study on Principal Component Analysis for Clustering Gene Expression Data’, Technical Report, Dept. of Computer Science and Engineering, University of Washington.
Yogeesh N. "Study on Clustering Method Based on K-Means Algorithm." Journal of Advances and Scholarly Researches in Allied Education (JASRAE), vol. 17, no. 1, 2020, pp. 485-489(5), www.ignited.in//I/a/305304.
Jolliffe I.T. (1986), ‘Principal Component Analysis’, Springer-Verlag, Second edition, New York.
Yogeesh N. "Mathematical Approach to Representation of Locations Using K-Means Clustering Algorithm." International Journal of Mathematics And its Applications (IJMAA),
Published
How to Cite
Issue
Section
Copyright (c) 2022 International journal of health sciences
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published in the International Journal of Health Sciences (IJHS) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant IJHS right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.
Articles published in IJHS can be copied, communicated and shared in their published form for non-commercial purposes provided full attribution is given to the author and the journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
This copyright notice applies to articles published in IJHS volumes 4 onwards. Please read about the copyright notices for previous volumes under Journal History.
