Classification Data of Binary Data Respond to the Diagnosis of Lymphocytic Leukemia using Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA)

Fatma A. Abdelati Hanaa T. Elgohari Ali Y.AL-Zubaidi

Abstract: In this research, the process of distinguishing or categorizing statistical data was studied by using the dual-response Support vector machine and Linear discriminating function, by based on the correct classification, The two methods were then applied to the practical side and to real data of lymphocytic leukemia in Iraq, comparison was also made between the two methods used in the study. The study found that the method or method of the supporting vector machine was the best in the classification whether using the real data in the practical application side.

Keywords: lymphocytic leukemia, classification, SVM, LDA

Edition: Volume 8 Issue 2, February 2019,

Pages: 260 - 268

Expected Maximization Algorithm for Classification

Sripriya Muppidi | Bhatracharyulu N.Ch.

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Research Paper, Statistics, India, Volume 12 Issue 2, February 2023

Pages: 905 - 909

Designing a better Support Vector Machines Classification Model for Multi-Class Category

Muthukrishnan .R | Udaya Prakash .N

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Classification Data of Binary Data Respond to the Diagnosis of Lymphocytic Leukemia using Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA)

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