https://github.com/jubinjacob03/heartdiseaseclassify-ml

Heart Disease Dataset Analysis & Classification using ML models such as linear, support vector machine, k-means, k-nearest neighbors and logistic regression.
https://github.com/jubinjacob03/heartdiseaseclassify-ml

data-analysis data-science data-visualization ipython-notebook kaggle-dataset kmeans knn linear-regression logistic-regression machine-learning matplotlib python seaborn support-vector-machine

Last synced: 3 months ago
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Heart Disease Dataset Analysis & Classification using ML models such as linear, support vector machine, k-means, k-nearest neighbors and logistic regression.

• Host: GitHub
• URL: https://github.com/jubinjacob03/heartdiseaseclassify-ml
• Owner: jubinjacob03
• License: mit
• Created: 2023-06-23T19:22:24.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-06-15T09:31:49.000Z (7 months ago)
• Last Synced: 2024-10-11T14:43:21.544Z (3 months ago)
• Topics: data-analysis, data-science, data-visualization, ipython-notebook, kaggle-dataset, kmeans, knn, linear-regression, logistic-regression, machine-learning, matplotlib, python, seaborn, support-vector-machine
• Language: Jupyter Notebook
• Homepage:
• Size: 2.11 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# HeartDiseaseClassify-ML

Heart Disease Dataset Analysis & Classification using  Machine Learning models such as linear regression, support vector machine, k-means, k-nearest neighbors and logistic regression  to predict cardiac diseases.

# Main Branch

- This branch contains all files for both branches [heartD-1](https://github.com/jubinjacob03/HeartDiseaseClassify-ML/tree/heartD-1) & [heartD-2](https://github.com/jubinjacob03/HeartDiseaseClassify-ML/tree/heartD-2)

- Machine Learning with different Regressions on different Dataset

- Branch heartD-1 

 -

      HD_Linear-Reg.ipynb: Jupyter Notebook file with python code.

      Heart Disease.csv: Dataset of Heart Disease in which Machine Learning was performed.

      heartD-1_singlecodefile.py: Single .py file which contains all python codes from notebook file (for easy copying of codes).

- Branch heartD-2 

 -

      HD2_Logistic,KNN,SVM-Reg.ipynb: Jupyter Notebook file with python code.

      heart disease classification dataset.csv: Dataset of Heart Disease in which Machine Learning was performed.

      heartD-2_singlecodefile.py: Single .py file which contains all python codes from notebook file (for easy copying of codes).

# Setup and Running

- Install Any IDE which supports .ipynb and .py format.

- Import the .iypnb file along with dataset for respective branch (Check branch details to understand file structure for [each branch](#main-branch))

- Recommended IDE is [Jupyter Notebook](https://jupyter.org/), you can also use [Visual Studio Code](https://code.visualstudio.com/).

- If you are unable to import .iypnb file or the file is not supported. Then create a new .iypnb file.

- Copy the codes line by line from the singlecodefile.py for the respective Dataset and Notebook file. 

# Help and Reference

- Handling [.ipynb](https://fileinfo.com/extension/ipynb) files.

- About [Machine Learning](https://www.ibm.com/topics/machine-learning).

- Info about [Numpy, Pandas, matplotlib, SciKit-Learn](https://towardsdatascience.com/top-5-machine-learning-libraries-in-python-e36e3e0e02af).