Authors :
Tanbin Siddique Eidul; Md.Alim Imran; Amit Kumar Das
Volume/Issue :
Volume 7 - 2022, Issue 3 - March
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3OBktJ1
DOI :
https://doi.org/10.5281/zenodo.6486696
Abstract :
Nowadays, people often judge which
restaurant is good or bad by looking at the rating of the
restaurant. That’s why ratings are a critical factor in the
restaurant business. Ratings are usually given by people
judging by what kind of service restaurants are
providing. So, features of restaurants play a very
important role in this regard. The main goal of this
research is to predict ratings of restaurant business
based on features to help new entrepreneurs to set up
new business. We used different machine learning
algorithms like Decision tree, Support vector machine
(SVM), k-nearest neighbors’ algorithm (KNN),
Stochastic gradient descent (SGD), Gaussian Naive
Bayes. We also used a convolutional neural network
(CNN) model here. It gives us an accuracy score of 97.2
25 percent which is higher than all other algorithms.
Keywords :
machine learning algorithm, convolutional neural network (CNN).
Nowadays, people often judge which
restaurant is good or bad by looking at the rating of the
restaurant. That’s why ratings are a critical factor in the
restaurant business. Ratings are usually given by people
judging by what kind of service restaurants are
providing. So, features of restaurants play a very
important role in this regard. The main goal of this
research is to predict ratings of restaurant business
based on features to help new entrepreneurs to set up
new business. We used different machine learning
algorithms like Decision tree, Support vector machine
(SVM), k-nearest neighbors’ algorithm (KNN),
Stochastic gradient descent (SGD), Gaussian Naive
Bayes. We also used a convolutional neural network
(CNN) model here. It gives us an accuracy score of 97.2
25 percent which is higher than all other algorithms.
Keywords :
machine learning algorithm, convolutional neural network (CNN).
