This is a Jupyter Notebook in which I compare multiple classification methods in Python using UCI's Wisconsin breast cancer dataset for prediction. The candidate methods that I analyze and compare are:
- k-Nearest Neighbors (k-NN) 🙋♂️
- Decision Trees 🌲
- Random Forest 🌴🌲🌳
- Polynomial Kernel Support Vector Machines (SVMs) 📈
- Gaussian Kernel (RBF) Support Vector Machines 📉
- Deep Neural Network w/ sigmoid activation function 🌎
- Deep Neural network w/ ReLu activation function 🌐
You can also find my report in a PDF attached in this repository.
Tools/libraries used:
- 🤖 scikit-learn
- 📒 Jupyter Notebooks
- 🐼 pandas