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Analysis of Breast Cancer Detection Techniques Using RapidMiner

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Proceedings of International Conference on Artificial Intelligence and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1164))

Abstract

One of the most widely spread diseases among women is the breast cancer. In past few years, the incidences of breast cancer kept on rising. At this point, diagnosis of the cancer is crucial. However, breast cancer is treatable if it is identified during the earlier stages. Classification of tumor in case of breast cancer is done using machine learning algorithms, viz. decision trees, regression, SVM, k-NN, and Naïve Bayes. Then, accuracy of these algorithms is compared to predict the class (benign, malignant) of tumor, and the most appropriate algorithm is suggested based on the results. Wisconsin Breast Cancer Diagnostic Dataset is used. The data has been preprocessed, split, and applied to respective models. Tenfold cross-validation is applied to determine the accuracies.

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Author information

Authors and Affiliations

  1. Amity School of Engineering and Technology, Amity University Gurgaon, Gurgaon, Haryana, 122413, India

    Adhish Nanda & Aman Jatain

Authors
  1. Adhish Nanda
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  2. Aman Jatain
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Corresponding author

Correspondence to Aman Jatain .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Maharaja Surajmal Institute of Technology, New Delhi, India

    Poonam Bansal

  2. Department of Electrical and Electronics Engineering, Maharaja Surajmal Institute of Technology, New Delhi, India

    Meena Tushir

  3. Department of Automation and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  4. Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi, India

    Rajeev Srivastava

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Nanda, A., Jatain, A. (2021). Analysis of Breast Cancer Detection Techniques Using RapidMiner. In: Bansal, P., Tushir, M., Balas, V., Srivastava, R. (eds) Proceedings of International Conference on Artificial Intelligence and Applications. Advances in Intelligent Systems and Computing, vol 1164. Springer, Singapore. https://doi.org/10.1007/978-981-15-4992-2_1

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