UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 7 Issue 5
May-2020
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2005295


Registration ID:
231479

Page Number

1160-1162

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Title

Data Driven Herb’s Product Recommendation Framework

Abstract

In this era, the burden of chronic disease is rapidly increasing worldwide. Also varieties of disease are on rise. This eventually makes the prediction of disease extremely vital. The main ideology is to predict the disease and recommend the medication by analyzing the symptoms provided by the user as an input. As Ensemble method improves the result by combining multiple models, this makes us use K-Nearest Neighbor, Naïve Bayes and Random Forest for disease prediction. This also focuses on the recommendation of Herbs’ products in accordance with the predicted disease.

Key Words

Data Mining, Naïve Bayes, K-Nearest Neighbor (KNN), Random Forest,

Cite This Article

"Data Driven Herb’s Product Recommendation Framework", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.1160-1162, May-2020, Available :http://www.jetir.org/papers/JETIR2005295.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Data Driven Herb’s Product Recommendation Framework", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp1160-1162, May-2020, Available at : http://www.jetir.org/papers/JETIR2005295.pdf

Publication Details

Published Paper ID: JETIR2005295
Registration ID: 231479
Published In: Volume 7 | Issue 5 | Year May-2020
DOI (Digital Object Identifier):
Page No: 1160-1162
Country: pune, Maharastra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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