Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Aggregate Rating Prediction for Restaurants using regression techniques.

Aggregate Rating Prediction for Restaurants using regression techniques.

Khurshid, Syyada Shumaila

Paperback

General Computers

Currently unavailable to order

ISBN13: 9798344042404
Publisher: Independently Published
Published: Oct 22 2024
Pages: 62
Weight: 0.37
Height: 0.13 Width: 8.50 Depth: 11.00
Language: English
Food supply is a fast-growing industry, as the enthusiasm to taste different kinds of food increases in people, the industry develops itself. The development of any business requires learning, learning from past mistakes and never making the mistake that makes a good business. In this paper, we take the worldwide spread data of the restaurants and their cuisines with their locations from Zomato API an online food delivery service. Zomato provides the restaurant data with the Aggregate rating and the features that affect the rating. These features that help to grow a restaurant business are clearly explained and these features are implemented into regression models which help to predict the aggregate rating of a restaurant. The best prediction model that can be applied to the data is evaluated using some metric values. This paper also gives you, details about the top 10 popular cuisines in the particular region within the 15 countries data we have. The extended study of this paper can also help build a successful restaurant business with the appropriate data and usage of it.

Also in

General Computers

View All