dashboard/:
Contains all the Streamlit app components (app.py, overview.py, filtered.py, model_result.py, prediction.py) for building the interactive dashboard.
alzheimers_disease_data.csv:
The primary dataset used for analysis and training.
Correlation-Accuracy_Results:
Folder with the results from the GA,the best correlation and accuracy from each run
GA2.ipynb:
Genetic Algorithm used to select features.
models.ipynb:
Trains and evaluates ML models using selected features from GA.
models2.ipynb:
Trains and evaluates models using all features for comparison.
metrics.csv:
Contains saved metrics like accuracy from different models using the selected features
preprocessing.ipynb:
Handles missing values, scaling, and other preprocessing steps.
requirements.txt:
List of libraries needed to run the code.
results.txt:
Contains the accuracy, correlation and features selected from each run
Selected_features.csv:
The final selected features after applying genetic algorithm optimization.
Tradeoff_plot.png:
Visual representation of the trade-off between accuracy and correlation results from GA.