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https://github.com/ofir-frd/predict-success-of-a-restaurant

Apply machine learning on a restaurante database. Study and analyse the data for prediction of a successful restaurant.
https://github.com/ofir-frd/predict-success-of-a-restaurant

data-analysis data-science machine-learning visualization

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Apply machine learning on a restaurante database. Study and analyse the data for prediction of a successful restaurant.

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# Machine-Learning-Predict-Success-of-a-Zomato-Restaurant
Experimanting in machine learning on a restaurante database. Study and analyse the data for prediction of a successful restaurant.


Restaurans Geolocation:

![2](https://user-images.githubusercontent.com/85901822/127760558-a304ada2-9f0e-4684-ab54-51aea961c9e9.PNG)

Popular meals:

![Figure 2021-07-30 132054](https://user-images.githubusercontent.com/85901822/127639410-f28140f6-8e13-4312-b657-9811378cc84f.png)

Popular comments:

![Figure 2021-07-30 174743](https://user-images.githubusercontent.com/85901822/127670696-8753bbde-f271-4e8b-8a48-2b8f1f1b5339.png)

Top 5 most and least expensive restaurants:

![Top5Price](https://user-images.githubusercontent.com/85901822/133610290-cf51a142-9028-4fd1-b38b-b300dc065efd.png)

Top 5 most and least voted restaurants:

![Top5Voted](https://user-images.githubusercontent.com/85901822/133610343-51a52dff-1657-4305-82b9-82f1cc57fb85.png)

Statistics on orders availability:

![Orders](https://user-images.githubusercontent.com/85901822/133610463-9be9d13e-871b-400d-9003-6580f316e12a.png)

Most common restaurant type:

![MajorFood](https://user-images.githubusercontent.com/85901822/133610535-7db193a3-933f-47d8-bf60-e0017cca215d.png)

Confusion matrix and accuracy score per method:

LogisticRegression
[[3523 1664]
[ 719 2349]]
0.71

Naive Bayes
[[3950 2481]
[ 292 1532]]
0.67

RandomForest
[[3193 1402]
[1049 2611]]
0.70

DecisionTree
[[3432 1505]
[ 810 2508]]
0.72

KNN
[[3183 1360]
[1059 2653]]
0.71

xg
[[3183 1360]
[1059 2653]]
0.71