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https://github.com/AyeshaShafique/Breast-Cancer-Study
https://github.com/AyeshaShafique/Breast-Cancer-Study
breast-cancer-prediction machine-learning machine-learning-algorithms model-comparsion python
Last synced: 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/AyeshaShafique/Breast-Cancer-Study
- Owner: AyeshaShafique
- Created: 2018-12-11T10:39:32.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2018-12-11T13:43:08.000Z (about 6 years ago)
- Last Synced: 2024-08-05T10:08:23.379Z (6 months ago)
- Topics: breast-cancer-prediction, machine-learning, machine-learning-algorithms, model-comparsion, python
- Language: Jupyter Notebook
- Size: 37.1 KB
- Stars: 2
- Watchers: 2
- Forks: 2
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-ai-cancer - AyeshaShafique/Breast-Cancer-Study - An experiment comparing the precision of MLP, XGBoost Classifier, Random Forest, Logistic Regression, SVM Linear Kernel, SVM RBF Kernel, KNN, and AdaBoost in classifying breast tumors (Code / Repositories)
README
# Breast-Cancer-Study
Breast Cancer data of 683 women was obtained from the UC Irvine Machine Learning Repository. Eight different machine learning classification models were trained using Breast Cancer data. Sensitivity, precision and F1 score for each class and overall accuracy of each model were obtained to predict Malignant and Benign tumors. Model with the best performance on specified metrics was then recognized.