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Classification of Medical Datasets Using Optimal Feature Selection Method with Multi-support Vector Machine

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Advancements in Smart Computing and Information Security (ASCIS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1759))

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Abstract

Automated Diagnosis in healthcare is becoming an interesting study in recent time among the data scientists to predict and diagnose the conditions in patients. In this manner, analysis of plays a major part in detection and classification of disease and accurately diagnose the medical condition in patients. Most of the data mining task is held up with poor classification accuracy due to the presence of redundant or irrelevant data items. In this research, the issue of poor classification accuracy is addressed and is solved by developing a framework that involves a series of stages. This includes pre-processing, feature extraction and classification of data items. The study uses Optimal Feature Selection Method (OFSM) as its feature selection tool and Multi-Support Vector Machine as its classification tool. The experimental validation is carried out to study the efficacy of the proposed method over various datasets and the outputs are evaluated in terms of accuracy, specificity, sensitivity and f-measure.

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Authors and Affiliations

  1. Department of Computer Science, Bharath Institute of Higher Education and Research (BIHER), Chennai, Tamilnadu, India

    S. Silvia Priscila

  2. Department of Computer Science, Bishop Heber College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli, Tamilnadu, India

    C. Sathish Kumar

Authors
  1. S. Silvia Priscila
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  2. C. Sathish Kumar
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Corresponding author

Correspondence to S. Silvia Priscila .

Editor information

Editors and Affiliations

  1. Marwadi University, Rajkot, India

    Sridaran Rajagopal

  2. AVPTI, Rajkot, India

    Parvez Faruki

  3. Marwadi University, Rajkot, India

    Kalpesh Popat

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Priscila, S.S., Kumar, C.S. (2022). Classification of Medical Datasets Using Optimal Feature Selection Method with Multi-support Vector Machine. In: Rajagopal, S., Faruki, P., Popat, K. (eds) Advancements in Smart Computing and Information Security. ASCIS 2022. Communications in Computer and Information Science, vol 1759. Springer, Cham. https://doi.org/10.1007/978-3-031-23092-9_18

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  • DOI: https://doi.org/10.1007/978-3-031-23092-9_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23091-2

  • Online ISBN: 978-3-031-23092-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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