https://github.com/rohanpunjani/aprioridatavisualization

https://github.com/rohanpunjani/aprioridatavisualization

Last synced: 20 days ago
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• Host: GitHub
• URL: https://github.com/rohanpunjani/aprioridatavisualization
• Owner: RohanPunjani
• Created: 2021-04-30T07:09:47.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2021-06-24T09:44:49.000Z (over 3 years ago)
• Last Synced: 2024-10-29T22:38:34.536Z (2 months ago)
• Language: JavaScript
• Size: 608 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# AprioriDataVisualization

It is a Data Mining Project in order to handle data and present it on a webpage.

The UI design is still in progress, here's a sneak peek of the frontend part

![apriori](https://user-images.githubusercontent.com/48467821/123241342-ad58ed00-d4fe-11eb-89af-f6ee64b17f83.png)

# Association Rules

Association Rules has 3 important rules:

- Support: This measure defines the likeliness of occurrence of consequent on the cart given that the cart already has the antecedents.

- Cofidence: This measure gives an idea of how frequent an itemset is in all the transactions

- Lift: Lift controls for the support (frequency) of consequent while calculating the conditional probability of occurrence of {Y} given {X}.

There is another rule known as conviction: 

- Conviction: It compares the probability that {X} appears without {Y} if they were dependent with the actual frequency of the appearance of {X} without {Y}.

## Aim

My Aim was to give user all these details when a product is selected, so I made something like this:

![image](https://user-images.githubusercontent.com/48467821/123241408-c3ff4400-d4fe-11eb-9946-c441c63887d1.png)

All the data that you are seeing in this image actually comes from the algorithm that we have ran on the backend app.py file

# How to run

1. Clone the repo

2. Go to the repo directory

3. Run backend:

    1. Open Terminal

    2. Type cmd: `python app.py`

    3. If it gives errors like `module not found`, install the module using pip install `module`. Replace `module` with the error module.

4. Run Frontend:

    1. Create new terminal

    2. Go to client folder

    3. Type cmd: `npm install`

    4. Type cmd: `npm start`

5. Enjoy

If you like this repo, check out my profile at [github.com/RohanPunjani](https://github.com/RohanPunjani). 

Thank You for making it this far XD