Comparative Study of Support Vector Machine and Naïve Bayes Classification Algorithm on Amazon Data
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2019 by IJCTT Journal|
|Year of Publication : 2019|
|Authors : Priyanka Tyagi, R.C Tripathi|
|DOI : 10.14445/22312803/IJCTT-V67I12P106|
MLA Style:Priyanka Tyagi, R.C Tripathi "Comparative Study of Support Vector Machine and Naïve Bayes Classification Algorithm on Amazon Data" International Journal of Computer Trends and Technology 67.12 (2019):24-27.
APA Style Priyanka Tyagi, R.C Tripathi. Comparative Study of Support Vector Machine and Naïve Bayes Classification Algorithm on Amazon Data International Journal of Computer Trends and Technology, 67(12),24-27.
This paper explores the comparison of support vector machine and Naïve Bayes classification algorithm on the basis of accuracyand confusion matrix parameter. This paper consider sentimental review of Amazon prime movies. This paper shows the SVM achieve substantial performance over Naïve Bayes and behave robustly over a different parameter of matrix.To extract the data Tweepy api application software is used . Tweepy is open sourced and enables python to communicate with twitter and used its API and extracted data stores in csv files.Twitter character length is extend to 280 from 140 in 2018.The most common length of tweet is 33 character only.Only 12% of tweets hit twitter’s 140 character limit.Only 1% of tweets hit twitter’s 240 character limit.
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introduction, methodology, metrics, implementation, future scope