Mis on probleem lahendusega, millel on sisemine tsükkel O(n^2)?

The solution with a nested loop in O(n²) is often inefficient for large data volumes, as execution time grows quadratically with the size of the input data. This leads to significant delays and high resource load.

Problems of this approach:

• Low scalability: increasing n tenfold will increase the processing time by 100 times.
• High CPU load: especially critical for real-time or large datasets.
• Inefficiency: nested loops can often be replaced with more efficient algorithms using hash tables, sorting, or other data structures.

For example, instead of searching for pairs with a certain property via a nested loop, a dictionary can be used for quick search in O(n) time.

Optimizing the algorithm reduces complexity and improves performance, which is important in machine learning and other computationally intensive tasks.