Suppose you are working on a project where you need to optimize the selection of features within a limited budget. How would you apply the concepts of the Knapsack Problem to address this scenario?
- Assigning values to features based on their importance and selecting features that maximize the total value within the budget.
- Assigning weights to features based on their complexity and selecting features that maximize the total weight within the budget.
- Including all available features within the budget without optimization.
- Randomly selecting features for inclusion.
Applying Knapsack concepts to feature selection involves assigning values to features and selecting features to maximize the total value within a limited budget, ensuring the optimal use of resources.
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