Differential Privacy
Machine Learning
A population-based optimization algorithm that evolves solutions through vector differences between population members.
Detailed Explanation
Differential Evolution is an optimization algorithm within machine learning that iteratively improves candidate solutions by combining existing solutions based on the differences between population members. It uses mutation, crossover, and selection processes to explore the solution space efficiently, making it effective for complex, multidimensional problems where traditional methods may struggle to find optimal solutions.
Use Cases
- •Optimizing hyperparameters in neural networks efficiently for improved model performance.
Related Terms
Other terms in the Machine Learning category