Spam Email Detection Using Machine Learning

Abstract

Machine learning is a limb of artificial intelligence (AI) and information technology. Supervised machine learning is a subcategory of artificial intelligence and also the machine learning which is branch of (AI). The supervised learning always utilizes on labeled data that can train algorithm to accurately predict the results and classify data. Now a days day by day technology is more positive and negative also. In that the negativity one is spam mail which is under phishing and this can be recover with machine learning algorithms because it provides a perfect test result for detect spam mail. The goal of this study case that here describes the way that detect spam mail through the algorithms and applying them visually. Here we preferred Logistic Regression (LR), Support Vector Machine (SVM), Naïve Bayes (NB), Random Forest (RF) algorithms. Then after testing Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes these all algorithm gives this accuracy frequently 98 %, 96% and 0%. The rest of one algorithm is discuss with figures. After testing data Support Vector Algorithm gives highest accuracy which is 98%