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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi ELECTRANS JMECS (Journal of Measurements, Electronics, Communications, and Systems) Journal of Community Practice and Social Welfare (JaCiPS) Prosiding Konferensi Nasional PKM-CSR Indonesian Journal of Physics (IJP) eProceedings of Engineering Telkatika: Jurnal Telekomunikasi Elektro Komputasi & Informatika
Ig. Prasetya Dwi Wibawa
Universitas Telkom
Humanities Astronomy Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Nursing Public Health Social Sciences Other

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Journal : CAUCHY: Jurnal Matematika Murni dan Aplikasi

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Enhancing Binary Classification Performance in Biomedical Datasets: Regularized ELM with SMOTE and Quantile Transforms Focused on Breast Cancer Analysis Aina, Brilliant Friezka; Kallista, Meta; Wibawa, Ig. Prasetya Dwi; Nugroho, Ginaldi Ari; Meiska, Ivana; Naf’an, Syifa Melinda
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 2 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i2.28785

Abstract

Using microarray datasets, this research investigation addresses the problem of unbalanced data in binary classification tasks. The objective is to increase classification performance by adding Extreme Learning Machine (ELM) regularization, as well as Synthetic Minority Over-sampling Technique (SMOTE) for data over-sampling and Quantile Transformer for data scaling. The study began with gathering important biological datasets from reputable sources such as UCI and Kaggle, including Pima Indian Diabetes, Heart Disease, and Wisconsin Breast Cancer. SMOTE was employed to solve the difficulty of data imbalance in the preparation of the dataset. The data was then separated into training (80%) and testing (20%) sets before being scaled using Quantile Transformation. To boost accuracy, ELMs were employed with an emphasis on introducing regularization techniques. Quantile Transforms are used to generate a Gaussian or uniform probability distribution from numerical input variables. Regularized ELM (R-ELM) surpasses ELM in terms of AUC, despite ELM's faster calculation time. The final selection of the regularization parameter (C) in R-ELM influences the model's performance and calculation time. Overall, R-ELM with SMOTE produces encouraging results when it comes to effectively categorizing biological dataset properties. A subsequent investigation and validation of additional datasets, however, are necessary to establish its generalizability and robustness.
Co-Authors Abdul Latif, Muhammad Achmad Rizal Addinul Rafif Nufrinal Aditya, Muhammad Billy Adnanqays G. Riyadhi Adnanqays Graha Riyadhi Agung Surya Wibowo Aina, Brilliant Friezka Akbar, Andi Muhammad Rezky Akbar, Muh. Aldila Ersa Samapta Amanullah Bahtiar, Mohammad Rizky Fauzan An – Nisaa, Siti Andre Suryaputra Angga Rusdinar Asry Fahriza Hani Pinem Cahyantari Ekaputri Dami Mahardiwana Desri Kristina Silalahi Dhani Eka Putra Subekti Edwar Ekki Kuniawan Ekki Kurniawan Epo Ilham Ajiprasetyo Erwin Susanto Ester Roselin Ambarita Fajar Ridho Wicaksono Fajar Surya Permana Falih Asyrafi Fanio Prambudi Fatanaja Abrar, Hanan Fiky Y. Suratman Fujitson Simamora Ganga Ram Phaijoo Gede Eka Adi Sanjaya Hamiedah, Muthi’ah Atsari Harry Wijaya Fauzi Hilmy Dzul Faqar Ijon Posmarohatta Sinaga Indra Laksana Irfan Fauzi Aristianto Junartho Halomoan Khalid Irta Tamara Khalisheka, Daffa Asyqar Ahmad Kusumah, Zaky Ibnu Lulu Danisia M. Bayu Oktodwilavito Martuahman, Fransiskus Alexander Meiska, Ivana Meta Kallista Michael Miftah Abdullah Mohamad Ramdhani Mohammad Ramdhani Muh Ichsan Kamil Muhammad Arsil Ghafur Muhammad Iqbal Muhammad Irfaan Hadi Muhammad Reza Elang Erlangga Muhammad Reza Hammady Muhtar, Ahmad Fauzan Mulia, Thasya Naf’an, Syifa Melinda Neina Oktavia Sariningsih Nugroho, Ginaldi Ari Porman Pangaribuan Purnama, Badi Rafli Rizky Putra, Aditiya Nicola Putra, Giovano Trihade Putra, Rio Mandala Nuryan Ramdhan Nugraha Ramdhan, Mohammad Rizki Ramdhani, Agung Sulaksono Rebecca Chittra Widyaparamitha Reza Aristyo Pramudita Rezza Aji Saputra Ria Juliani Dewi Rifki Nurgraha Rio Fernando Rizki Ardianto Priramadhi Sagita, Elvira Saputra , Ariq Nurcahyo Septa Muhammad Rivaldy Sony Sumaryo Sugandi, Delatifa Putri Sukiman, Wahyu Mubarak Wahid, Zulian Wahmisari Priharti Wardhana, I Made Bayu Satria Yasir , Yusran Yusuf Pratama Ari Wiyono Zulaikha Zulaikha Zulfany, Aprilla Nurindah