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Email Spam Filtering Model with the Machine Learning Models
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The increase in the volume of the unrequired emails which can be termed as the spam has started an issue for the development or implementation of the model for detecting the spam emails and named as the anti-spam filters. The various Machine learning models or the algorithms can be used for the success full detection of the spam emails. In this paper we will present the systematic approach of some of the best machine learning model based email spam filtering techniques. After implementing these models we will propose a bet model for the spam filtering as per the accuracy of the algorithm. We first discuss about the importance of the machine learning algorithms and various models suitable for the spam filtering. Then with the help of the dataset we will implement all the algorithms and finally proposed the best algorithm according to the results like high accuracy. Finally the results of all the suitable algorithms are presented in the paper. Then conclude and propose the best algorithm.
Title: Email Spam Filtering Model with the Machine Learning Models
Description:
The increase in the volume of the unrequired emails which can be termed as the spam has started an issue for the development or implementation of the model for detecting the spam emails and named as the anti-spam filters.
The various Machine learning models or the algorithms can be used for the success full detection of the spam emails.
In this paper we will present the systematic approach of some of the best machine learning model based email spam filtering techniques.
After implementing these models we will propose a bet model for the spam filtering as per the accuracy of the algorithm.
We first discuss about the importance of the machine learning algorithms and various models suitable for the spam filtering.
Then with the help of the dataset we will implement all the algorithms and finally proposed the best algorithm according to the results like high accuracy.
Finally the results of all the suitable algorithms are presented in the paper.
Then conclude and propose the best algorithm.
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