JP Journal of Biostatistics

The JP Journal of Biostatistics is a highly regarded open-access international journal indexed in the Emerging Sources Citation Index (ESCI). It focuses on the application of statistical theory and methods in resolving problems in biological, biomedical, and agricultural sciences. The journal encourages the submission of experimental papers that employ relevant algorithms and also welcomes survey articles in the fields of biostatistics and epidemiology.

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COMPARING ACCURACY OF LOGISTIC REGRESSION, K-NEAREST NEIGHBOR, SUPPORT VECTOR MACHINE, AND NAÏVE BAYES MODELS USING TRACKING ENSEMBLE MACHINE LEARNING

Authors

  • Kuntoro Kuntoro

Keywords:

accuracy, tracking ensemble, feature, target, SVM.

DOI:

https://doi.org/10.17654/0973514324001

Abstract

Selecting model for classifying target correctly is important. Logistic regression (LR), K-nearest neighbor (KNN), Support vector machine (SVM), and Naïve Bayes (NB) are base models in classifying target. Tracking ensemble is the method for comparing accuracy in machine learning.

Datasets are generated by a code of Python as recommended by Brownlee [1]. Five sample sizes of 1,000, 3,000, 5,000, 7,000, and 10,000 are selected. The number of features is 20 having informative and redundant features, respectively, as 15 and 5.

The result shows that support vector machine (SVM) has the highest mean of accuracy and the lowest coefficient of variation of accuracy in all sample sizes. Naïve Bayes (NB) has the lowest mean of accuracy and the highest coefficient of variation of accuracy in all sample  sizes. It is recommended to select support vector machine (SVM) for classifying target.

Received: August 13, 2023
Accepted: October 9, 2023

References

J. Bownlee, Stacking Ensemble Machine Learning with Python, 2021.

https://machinelearningmastery.com/stacking-ensemble-machine-learning-with-python/100823.

S. Greenland, R. Daniel and N. Pearce, Outcome modelling strategies in epidemiology: traditional methods and basic alternatives, International Journal of Epidemiology 45(2) (2016), 565-575.

Java T Point, Regression vs Classification in Machine Learning, 2023.

https://www.javatpoint.com/regression-vs-classification-in-machine-learning. 110823.

E. Lutin, Ensemble Methods in Machine Learning: What are They and Why Use Them? 2017.

https://towardsdatascience.com/ensemble-methods-in-machine-learning-what-are-they-and-why-use-them-68ec3f9fef5f 110823.

S. Ray, Naïve Bayes Classifier Explained: Application and Practice Problems of Naïve Bayes Classifier, 2017.

https://www.analyticsvidhya.com/blog/2017/09/naive-bayes-explained/.

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Published

2023-10-26

Issue

Vol. 24 No. 1 (2024)

Section

Articles

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How to Cite

COMPARING ACCURACY OF LOGISTIC REGRESSION, K-NEAREST NEIGHBOR, SUPPORT VECTOR MACHINE, AND NAÏVE BAYES MODELS USING TRACKING ENSEMBLE MACHINE LEARNING. (2023). JP Journal of Biostatistics, 24(1), 1-13. https://doi.org/10.17654/0973514324001

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