Rating Prediction Classification using Machine Learning Techniques

Reena Sahu; Kranti Kumar Dewangan

Rating Prediction Classification using Machine Learning Techniques

Authors: Reena Sahu, Kranti Kumar Dewangan

Unique Paper ID: 154850
Volume: 8
Issue: 12
PageNo: 548-552

Keywords: Natural Language processing Diabetes prediction classification.

Abstract:
Natural language Processing (NLP) is an interdisciplinary space which is worried about getting normal dialects along with utilizing them to empower human-PC cooperation. Normal dialects are innately intricate and numerous NLP undertakings are badly modeled for numerically exact algorithmic classifications. With the appearance of enormous information, information driven ways to deal with NLP issues introduced another worldview, where the intricacy of the issue area is actually overseen by utilizing huge datasets to construct straightforward however great models. In this theory, we examine information about the business rating from Yelp, explicitly the surveys, to foresee rating of the business from 1 to 5 in light of the substance of the audits. Our outcomes depend on performing opinion examination on the surveys, which includes dissuade mining the effect of the audit in numbers. The "stars" section is the quantity of stars (1 through 5) doled out by the commentator to the business. (Higher stars are better.) all in all, it is the rating of the business by the individual who composed the survey. The "cool" segment is the quantity of "cool" casts a ballot this audit got from other Yelp clients. We have utilized the innocent based classifier to foreseeing the rating of the business.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 12
PageNo: 548-552

Rating Prediction Classification using Machine Learning Techniques

Available:https://ijirt.org/Article?manuscript=154850

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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