An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic
Volume-3 | Issue-3
Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Population Based Meta Heuristics Algorithm for Performance Improvement of Feed Forward Neural Network
Volume-2 | Issue-1
Comparative Analysis of an Efficient Image Denoising Method for Wireless Multimedia Sensor Network Images in Transform Domain
Volume-3 | Issue-3
A Comprehensive Review on Power Efficient Fault Tolerance Models in High Performance Computation Systems
Volume-3 | Issue-3
An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet
Volume-3 | Issue-4
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach
Volume-3 | Issue-4
Acoustic Features Based Emotional Speech Signal Categorization by Advanced Linear Discriminator Analysis
Volume-3 | Issue-4
Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction
Volume-3 | Issue-4
Identification of Electricity Threat and Performance Analysis using LSTM and RUSBoost Methodology
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Volume - 4 | Issue - 2 | june 2022
Published
06 July, 2022
Recently, email has become a common way for people to communicate and share information both officially and personally. Email may be used by spammers to transmit harmful materials to Internet users. The data must be protected from unauthorized access, which necessitates the development of a reliable method for identifying spam emails. As a result, a variety of solutions have been devised. An innovative hybrid machine learning strategy for effectively detecting spam emails has been discussed in this study. This means that identifying spam and non-spam email is a difficult process. Spam email categorization has undergone a significant evolution in recent years, as shown by the research given below. For locating spam, this study uses a mixed approach. Different email categorization algorithms are used to rank them for future perspective.
KeywordsHybrid Neural Networks email spam classification Feature selection artificial bee colony ant colony optimization
Full Article PDF Download Article PDF