What are greedy algorithms in machine learning?

What are greedy algorithms in machine learning?

Greedy algorithms are a type of algorithm that makes the locally optimal choice at each stage with the hope of finding a global optimum.

Can you give me an example of a greedy algorithm used in machine learning?

Sure! One common example is the K-means clustering algorithm, which iteratively assigns data points to the nearest cluster center.

What are the advantages and disadvantages of using greedy algorithms?

Advantages include simplicity and speed, while disadvantages can be suboptimal solutions and lack of global perspective.

In what scenarios are greedy algorithms most effective?

They are most effective in optimization problems where local choices lead to a global solution, like in scheduling or resource allocation.