The correct answer is C. To find optimal solutions.
A genetic algorithm is a search heuristic that is inspired by the process of natural selection. It is used to find optimal solutions to problems that are difficult to solve using traditional methods.
Genetic algorithms work by iteratively creating a population of solutions, evaluating each solution, and then selecting the best solutions to create the next generation of solutions. This process is repeated until a satisfactory solution is found.
Genetic algorithms are often used to solve problems in machine learning, such as classification and regression. They can also be used to solve problems in other areas, such as scheduling, optimization, and design.
Here is a brief explanation of each option:
- Option A: To maximize the margin between classes. This is not the primary objective of a genetic algorithm. The primary objective of a genetic algorithm is to find optimal solutions.
- Option B: To minimize prediction errors. This is not the primary objective of a genetic algorithm. The primary objective of a genetic algorithm is to find optimal solutions.
- Option C: To find optimal solutions. This is the primary objective of a genetic algorithm. Genetic algorithms are used to find optimal solutions to problems that are difficult to solve using traditional methods.
- Option D: To visualize data relationships. This is not the primary objective of a genetic algorithm. Genetic algorithms are used to find optimal solutions to problems, not to visualize data relationships.