甲状腺-甲状腺分类：UCI甲状腺分类-​​Python，Keras，scikit-learn，ANN

## UCI Thyroid Classification - Python, Keras, scikit-learn, ANN This project is created for classification problem on UCI-Thyroid-Disease dataset. It uses ANN to make predictions. Prediction classes are: * 1-Hyperthyroid * 2-Subnormal * 3-Normal ### Data Sets * Thyroid disease [data set][ds] in UCI repository. ### Frameworks/Libraries * Keras * scikit-learn ### Getting Started These instructions will get you a brief idea on setting up the environment and running on your local machine for development and testing purposes. **Prerequisities** - python3.5 or newer - Keras - scikit-learn - numpy - pandas **Setup and running tests** 1. Run `python -V` to check the installation 2. Install all the required libraries. 3. Execute the following commands from terminal to run the tests: `python main.py` Note: Model accuracy - on validation: 98.57% (0.41%) and on test data: 98.279%. As per the dataset information any model with accuracy >92% is considered as a good one. Further improvement is definitely possible. [ds]: <https://archive.ics.uci.edu/ml/datasets/thyroid+disease>