https://github.com/avestura/scikit-heart-disease-classifier
💚 A heart disease classifier using 4 SVM kernels and decision trees, with PCA, ROC, pruning, grid search cv, confusion matrix, and more
https://github.com/avestura/scikit-heart-disease-classifier
confusion-matrix cost-complexity-pruning decision-tree decision-tree-classifier grid-search-cross-validation linear-kernel one-hot-encoding pca poly-kernel pruning rbf-kernel roc sigmoid-kernel svm svm-classifier
Last synced: 3 months ago
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💚 A heart disease classifier using 4 SVM kernels and decision trees, with PCA, ROC, pruning, grid search cv, confusion matrix, and more
- Host: GitHub
- URL: https://github.com/avestura/scikit-heart-disease-classifier
- Owner: avestura
- Created: 2020-12-10T20:47:16.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-12-10T20:47:47.000Z (over 4 years ago)
- Last Synced: 2025-01-13T17:32:55.671Z (4 months ago)
- Topics: confusion-matrix, cost-complexity-pruning, decision-tree, decision-tree-classifier, grid-search-cross-validation, linear-kernel, one-hot-encoding, pca, poly-kernel, pruning, rbf-kernel, roc, sigmoid-kernel, svm, svm-classifier
- Language: Jupyter Notebook
- Homepage:
- Size: 573 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: readme.md
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README
# Heart Disease Classifier
A heart disease classifier using Scikit-Learn.
## Methods, approaches and visualizations
- SVM Classification (linear, poly, rbf and sigmoid kernels)
- Decision Tree Classification
- One-Hot encoding
- Data Scaling
- Confusion Matrix charts
- Optimizing parameters via grid search cross validiation
- PCA
- ROC Charts
- Decision surface/region chart
- Cost complexity pruning
- Visual Decision Tree after and before pruning
## Data Set
- Documentation: [https://archive.ics.uci.edu/ml/datasets/Heart+Disease](https://archive.ics.uci.edu/ml/datasets/Heart+Disease)
- Download: [Download](https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.cleveland.data)