What is algorithmic complexity in machine learning?

What is algorithmic complexity in machine learning?

Algorithmic complexity refers to the computational resources required to solve a problem, often measured in time and space.

Why is it important to consider algorithmic complexity?

It's crucial because it affects the efficiency and scalability of machine learning models, especially with large datasets.

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

Sure! An example is the Support Vector Machine (SVM), which can be computationally intensive, especially with large feature sets.

How can I reduce algorithmic complexity in my models?

You can reduce complexity by using simpler models, feature selection, or dimensionality reduction techniques like PCA.