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Volume 3 | Issue 8

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Paper Title: Diagnosis of liver abnormalities using Support Vector Machine
Authors Name: Geeta Kadu , Dr. Ranjana Raut , Mr. Suraj S. Gawande3
Unique Id: IJRTI1807021
Published In: Volume 3 Issue 7, July-2018
Abstract: Many a times there is an incorrect diagnosis, specifically in rural areas, due to incorrect reading of clinical reports. For preliminary diagnosis Machine Learning Classification techniques are effectively used in medical field for finding abnormalities in many ailments. In this paper Support Vector Machine (SVM) a Supervised Machine Learning Classifier has been used for the demarcation of normal and diseased Liver. Since, data is not linearly separable, Non-Linear classifier is used. Kernel based SVM, such as Linear, quadratic, MLP, RBF and polynomial, with modified kernel functions are used. Indian Liver Patient Dataset (ILPD) is used for this work. Accuracy for various KFs is calculated. Finally the performance evaluation has been done where we compared the accuracy obtained from all the KF based SVM classifiers and the result is plotted.
Keywords: Classification techniques, Supervised machine learning, Support Vector Machine (SVM), Indian Liver Patient Dataset (ILPD), Kernel Functions (KF)
Cite Article: "Diagnosis of liver abnormalities using Support Vector Machine", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.3, Issue 7, page no.132 - 137, July-2018, Available :http://www.ijrti.org/papers/IJRTI1807021.pdf
Downloads: 00027
Publication Details: Published Paper ID: IJRTI1807021
Registration ID:180351
Published In: Volume 3 Issue 7, July-2018
DOI (Digital Object Identifier):
ISSN Number: 2456 - 3315
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