Cancer Prediction with Gene Expression Data
G Sivagamasundari1, Latha Parthiban2
1G Sivagamasundari, Research Scholar, School of Engineering and Technology, Pondicherry University, (Tamil Nadu), India.
2Latha Parthiban, Department of Computer Science, Pondicherry University CC, Puducherry (Tamil Nadu), India.
Manuscript received on 03 July 2019 | Revised Manuscript received on 13 August 2019 | Manuscript Published on 27 August 2019 | PP: 268-273 | Volume-8 Issue-2S4 July 2019 | Retrieval Number: B10500782S419/2019©BEIESP | DOI: 10.35940/ijrte.B1050.0782S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With continuous growth in technology and quantum of data, many data mining algorithms are developed that uses micro array data to classify the genes and expressions in normal and disease conditions. There are many clustering algorithms that help to classify the genes and there is conflict in large pool of genes and their expression characters. The proposed system takes the input from multiple sources produces associate storage, cluster the information and classify it.
Keywords: Data Mining, Gene Expression Data, Classification.
Scope of the Article: Regression and Prediction