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Created a model using Logistic Regression algorithm on Amazon Fine Food Review Dataset.

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Logistic-Regression-on-Amazon-food

Created a model using Logistic Regression algorithm on Amazon Fine Food Review Dataset.

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).

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Created a model using Logistic Regression algorithm on Amazon Fine Food Review Dataset.

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