Amazon Fine Food Review Save

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

Project README

The Amazon Fine Food Reviews dataset consists of reviews of fine foods from Amazon.

Number of reviews: 568,454 Number of users: 256,059 Number of products: 74,258 Timespan: Oct 1999 - Oct 2012 Number of Attributes/Columns in data: 10

Attribute Information:

Id

ProductId - unique identifier for the product

UserId - unqiue identifier for the user

ProfileName

HelpfulnessNumerator - number of users who found the review helpful

HelpfulnessDenominator - number of users who indicated whether they found the review helpful or not

Score - rating between 1 and 5

Time - timestamp for the review

Summary - brief summary of the review

Text - text of the review

Objective:

Given a review, determine whether the review is positive (rating of 4 or 5) or negative (rating of 1 or 2)

With the perception of text/review we predicted the polarity of review.In this project we applied various algorithm such as KNN,Naive Bayes,Logistic Regression,Support Vector machine,Decision trees,Random forest & GBDT ,LSTM .

Open Source Agenda is not affiliated with "Amazon Fine Food Review" Project. README Source: krpiyush5/Amazon-Fine-Food-Review

Open Source Agenda Badge

Open Source Agenda Rating