Retracted: Accurate SMS Spam Detection Using Support Vector Machine in Comparison with Logistic Regression

For performing SMS Spam Detection incorporating Support Vector Machine as well as logistic regression (LR) is done here. Depending on accuracy, analysis for sms spam detection dataset associated with 5573 sentences. Classification of sms spam detection is performed by a support vector machine whose...

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Bibliographic Details
Published in2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) pp. 1 - 5
Main Authors K, Ram Bheemesh, N, Deepa
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.04.2023
Online AccessGet full text
DOI10.1109/ICONSTEM56934.2023.10142266

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Summary:For performing SMS Spam Detection incorporating Support Vector Machine as well as logistic regression (LR) is done here. Depending on accuracy, analysis for sms spam detection dataset associated with 5573 sentences. Classification of sms spam detection is performed by a support vector machine whose sample takes (N=27) as well as Linear Regression whose sample takes (N=27), G-power generation is performed whose value takes 80%. SVM accuracy is 97.67% whereas LR takes accuracy to be 97.02%. Significant value of accuracy is 0.02 (p<0.05). SVM performs better in tracking down precision when contrasted with Logistic Regression.
DOI:10.1109/ICONSTEM56934.2023.10142266