Learning Advanced Ensemble Strategy Python Projects
TITLE :- ADVANCED ENSEMBLE LEARNING STRATEGY WITH DEEP DYNA-Q INTEGRATION
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Implementation plan:
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Step 1: Initially we load and preprocess the Augmented_health_Heart_Rate dataset.
Step 2: Next we Implement All four classifiers for model selection
Step 3: Next we Implement hyperparameter spaces and use grid search technique.
Step 4: Next we Implement predictions using methods like majority voting, averaging, stacking, oboosting.
Step 5: Next we Implement Deep Dyna-Q to optimize ensemble performance
Step 6: Next we train the model and predict the result.
Step 7: Finally, Generate the graph for,
7.1: Accuracy
7.2: Precision
7.3: Recall
7.4: F1 Score
7.5: AUC
Software Requirement:
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1. Development Tool: Python – 3.11.4
2. Operating System: Windows 10 (64-bit)
Dataset link:
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https://www.kaggle.com/datasets/shauk...
Note: -
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1. If the above plan does not satisfy your requirement, please provide the processing details, like the above step-by-step.
2. Please note that this implementation plan does not include any further steps after it is put into implementation.
3. If the above plan satisfies your requirement please confirm with us.
4. We make simulation type process only.
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