Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach

2017 ◽  
Vol 278 ◽  
pp. 13-24 ◽  
Author(s):  
Minmin Miao ◽  
Hong Zeng ◽  
Aimin Wang ◽  
Changsen Zhao ◽  
Feixiang Liu
Keyword(s):  
Feature Extraction ◽  
Spatial Frequency ◽  
Motor Imagery ◽  
Bayesian Classifier ◽  
Sparse Regression ◽  
Naïve Bayesian Classifier ◽  
Naive Bayesian ◽  
Naive Bayesian Classifier ◽  
Temporal Feature

scholarly journals E-Mail Spam Classification using Naive Bayesian Classifier

2021 ◽  
Vol 9 (VI) ◽  
pp. 5209-5214
Author(s):  
Mr. B. Krishna
Keyword(s):  
Bayesian Classifier ◽  
Spam Filtering ◽  
Naïve Bayesian Classifier ◽  
Naive Bayesian ◽  
Naive Bayesian Classifier ◽  
Naïve Bayesian ◽  
Filtering Technique ◽  
E Mail ◽  
Feature Extraction Technique

— E-mail spam is the very recent problem for every individual. The e-mail spam is nothing it’s an advertisement of any company/product or any kind of virus which is receiving by the email client mailbox without any notification. To solve this problem the different spam filtering technique is used. The spam filtering techniques are used to protect our mailbox for spam mails. In this project, we are using the Naïve Bayesian Classifier for spam classification. The Naïve Bayesian Classifier is very simple and efficient method for spam classification. Here we are using the Lingspam dataset for classification of spam and non-spam mails. The feature extraction technique is used to extract the feature. The result is to increase the accuracy of the system.

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