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spamclassifier's Introduction

SpamClassifier

by team-19

Team Members

Kunal Kataria-18BCP058 Mohit Gupta-18BCP064 Vyomesh Jethva-18BCP152D Jaydeep Sondarva-18BCP147D Neel Yadav-18BCP066

Dataset

https://archive.ics.uci.edu/ml/index.php total sms:5572 ham:4825 spam:747

Methodolgy

It uses countVectorizer for feature extraction and multinomial naivebayes as classifier.

Result

true positives (TP): 946 true negatives (TN): 9 false positives (FP): 7 false negatives (FN): 153 Accuracy of model is :0.9856502242152466

spamclassifier's People

Contributors

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Watchers

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