Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Search Strategy Activity

The video tutorial covers three main activities. The first activity explores why wrapper methods in feature selection cannot try all subsets and the challenges involved. The second activity delves into the concept of greedy search, explaining its broader application beyond just wrapper methods. This section is optional and may involve understanding simulated annealing. The third activity focuses on simulated annealing and its relevance to search algorithms, particularly in the context of subset selection for wrapper or filter methods.

Explain the concept of simulated annealing and its relevance to searching algorithms.

What is the relationship between simulated annealing and subset selection for wrapper methods?