International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 67 | Issue 12 | Year 2019 | Article Id. IJCTT-V67I12P106 | DOI : https://doi.org/10.14445/22312803/IJCTT-V67I12P106

Comparative Study of Support Vector Machine and Naïve Bayes Classification Algorithm on Amazon Data

Priyanka Tyagi, R.C Tripathi

Citation :

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 (IJCTT), vol. 67, no. 12, pp. 24-27, 2019. Crossref, https://doi.org/10.14445/22312803/IJCTT-V67I12P106

Abstract

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.

Keywords

introduction, methodology, metrics, implementation, future scope

References

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