What are some examples of heuristics used in machine learning?

What are some examples of heuristics used in machine learning?

Heuristics in machine learning are rules of thumb that help simplify decision-making. Examples include the greedy algorithm, which makes the locally optimal choice at each stage, and the k-nearest neighbors algorithm, which classifies data points based on the closest training examples.

Can you explain the greedy algorithm in more detail?

Sure! The greedy algorithm builds up a solution piece by piece, always choosing the next piece that offers the most immediate benefit. It's often used in optimization problems, like finding the shortest path in a graph.

What are the limitations of using heuristics?

Heuristics can lead to suboptimal solutions because they don't always consider the bigger picture. They may also be biased based on the initial conditions or assumptions.

Are there any specific machine learning models that rely heavily on heuristics?

Yes, models like decision trees and genetic algorithms often use heuristics to make decisions about splitting data or evolving solutions.