COMP9321 2019 T1 Group Project: Heart Disease

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Hanxu Wu (z5148463)
Hao Wu (z5132458)
Jinci Zhang (z5136172)
Mingda Liu (z5019749)

data - raw data

flask-app - backend

client - Vue front-end

heatmag.png: shows the correlation for each attribute.

logstic.py: contains 4 models without applying data redunction. Model trained are stored in .sav files

plots.py : contains functions to generate graphs to demo my models selections. Will add more graphs later

read_data.py : use this file to read the training data

use_model.py : are prepared for future usage. A function to read from saged models(.sav) and read from

front end input to and use the model to predict heart diseases.

master-------------------------------->: merge from develope branch stable versions

dev------------------->:merge from features branch

feature-visualize-------->: feature frontend/backend

feature-ML/DL------->: feature train the models

feature-plot------->: prepare the visualize data

feature-selection------->: select feature

frontend : bootstrap,Vue,chartjs

backend : flask

git clone https://github.com/hanxuwu/project-HeartDisease.git

> virtualenv .

for windows:

> .\Scripts\activate

for MacOs:

> source ./bin/activate

> pip3 install -r requirements.txt

python app.py

$ cd client

npm install

npm run dev

then open :

http://localhost:8080/#/

1.Drag the test data to the Data/heart folder.

To re-generate my final model. First remove final_model.sav

2.then run final_model.py which will generate my final model again and stored as final_model.sav.

3. Run read_model.py, which will read from the saved model and print the result.