Indonesian Journal of Data and Science
Vol. 4 No. 2 (2023): Indonesian Journal of Data and Science

Improving Multi-Class Classification on 5-Celebrity-Faces Dataset using Ensemble Classification Methods

Nurul Rismayanti (Universitas Muslim Indonesia)
Aulia Putri Utami (Universitas Muslim Indonesia)



Article Info

Publish Date
31 Jul 2023

Abstract

This study aims to compare the performance between Random Forest Classifier and Gaussian Naïve Bayes Classifier in classification. Several evaluation metrics such as accuracy, precision, recall, and F1-score were used to analyze the performance of both models. The dataset used has specific characteristics that influence the evaluation results. The research findings indicate that Random Forest Classifier outperforms Gaussian Naïve Bayes Classifier in most of the evaluation metrics. Random Forest Classifier achieves higher accuracy and better precision, recall, and weighted F1-score. However, it should be noted that Random Forest Classifier also has more outliers compared to Gaussian Naïve Bayes Classifier when visualized using boxplots. Therefore, in selecting a classification model, a trade-off between higher performance and sensitivity to outliers needs to be considered. Further statistical testing and advanced evaluation are required to gain a deeper understanding of the impact and interpretation of the obtained results. This study provides valuable insights into understanding the comparison between these two classification models and their implications in different contexts.

Copyrights © 2023






Journal Info

Abbrev

ijodas

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Description

IJODAS provides online media to publish scientific articles from research in the field of Data Science, Data Mining, Data Communication, Data Security and Data ...