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Analysis of Mathematical Model of Support Vector Machine Techniques for early Prediction of Medical Diseases
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| Author:
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, PAMULA RAJA KUMARI, POLAIAH BOJJA, ANAND GALLA, RANA PRATAP
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| Abstract:
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The mathematical model of Support Vector Machine (SVM) will strong foundation offers upright approach in solving data science problems. In the perspective of mathematics, the training input SVM build its mathematical model which is usage of the SVM as broadly categorized as classification, regression, novelty detection tasks, and feature reduction. Now–a-days in many medical fields the technique of SVM will be utilized to determine or predict. It resembles a Computer helped analysis framework to support radiologist to distinguish Abnormalities prior and all the more quickly. The principle goal is to ensure fidelity and replication of detailed grouping comes about when an alternate example is examined. The early forecast of medical diseases like, breast cancer, skin disease and additionally thyroid. Texture classification is play an essential part in computer aided diagnostic system; the applications incorporate medicinal picture investigation and understanding, remote detecting. In this paper the advancement of the computer aided diagnostic system by using the mathematical of the SVM for the classification of mass characterization in medical diseases in view of the model of Support Vector Machine and the results are carried out by utilizing R-Language programming.
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| Keyword:
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Mathematical Model of SVM, Medical Disease, R-Language Program
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.04.461
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| Download:
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