Enhancement of Logistic Regression Algorithm Applied in Email Spam Detection

Vince Anthony S. Carlos; John Cedric C. Pancho; Vivien A. Agustin

doi:10.36948/ijfmr.2024.v06i06.32374

Enhancement of Logistic Regression Algorithm Applied in Email Spam Detection

Author(s)	Vince Anthony S. Carlos, John Cedric C. Pancho, Vivien A. Agustin
Country	Philippines
Abstract	Logistic regression is a popular binary classification approach, but like any machine learning algorithms, it has its limitations and possible concerns such as class imbalance, large datasets, and overfitting, which reduce its accuracy and efficiency. This study enhanced the Logistic Regression algorithm's performance for email spam detection by addressing these problems using the techniques of Term Frequency-Inverse Document Frequency for class imbalance, Recursive Feature Elimination for large datasets, and Principal Component Analysis for overfitting concerns. TF-IDF improves feature representation, highlighting key terms that differentiate spam from non-spam. RFE systematically eliminates irrelevant features, reducing computational complexity and enhancing efficiency, particularly for large datasets. PCA mitigates overfitting by reducing the dimensionality of feature spaces, ensuring the model generalizes effectively to unseen data. The enhanced Logistic Regression model demonstrated a significant improvement in spam detection accuracy, achieving up to 98% accuracy with TF-IDF. RFE reduced training time while maintaining robust performance on large datasets, and PCA improved model generalization, reducing overfitting risks. The proposed enhancements successfully address the key limitations of traditional Logistic Regression models in spam detection. This refined approach improves predictive accuracy, computational efficiency, and robustness, making it highly applicable to real-world email security systems.
Keywords	Logistic Regression, Spam Detection, TF-IDF, Recursive Feature Elimination, Principal Component Analysis, Machine Learning
Field	Computer
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-17
Cite This	Enhancement of Logistic Regression Algorithm Applied in Email Spam Detection - Vince Anthony S. Carlos, John Cedric C. Pancho, Vivien A. Agustin - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32374
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.32374
Short DOI	https://doi.org/g8wkpr

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Enhancement of Logistic Regression Algorithm Applied in Email Spam Detection

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