readme updated

README.md

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