This project focuses on lung cancer prediction using machine learning. It involves data preprocessing, splitting the dataset into training, testing, and validation sets, and building a predictive model.
- Data preprocessing and cleaning
- Splitting dataset for training, validation, and testing
- Building and training a machine learning model
- Evaluating model performance
To run this project, install the required Python libraries:
pip install numpy pandas scikit-learn matplotlib seaborn tensorflow keras- Load the dataset.
- Preprocess and clean the data.
- Split the dataset into training, testing, and validation sets.
- Train the model using the provided notebook.
- Evaluate model performance and make predictions.
Open the Colab Notebook and execute the cells step by step to preprocess the data, train the model, and evaluate results.
The model's performance is assessed using metrics like accuracy, precision, recall, and confusion matrix.
Feel free to contribute by improving the model or optimizing the data preprocessing steps.
This project is open-source and available for public use and modification.