Deep Neural Network Spam Email Classifier
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Updated
Jul 18, 2020 - Jupyter Notebook
Deep Neural Network Spam Email Classifier
Final project of the Machine Learning course at the University of Cagliari in 2022. Analysis of a dataset, use of Machine Learning techniques with Oversampling and Undersampling techniques. Final report with the results obtained.
This repository contains a detailed analysis of the Spambase Dataset using different classification algorithms, including Logistic Regression, Logistic Regression with Backward Feature Elimination (BFE), Support Vector Machine (SVM), SVM with Normalized Data, Decision Trees, Random Forest, K-Nearest Neighbors (K-NN), and K-NN with Normalized Data.
Data Analysis project based on the classification between Spam and No-Spam emails.
This is the 3rd Assignment of Statistical Methods in AI, 5th semster, IIITH
Email Spam detection using KNN and Decision Trees Models Trained using the Spambase database
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