How do different algorithms compare in terms of accuracy?

How do different algorithms compare in terms of accuracy?

The accuracy of algorithms can vary significantly based on the dataset and the problem type. Are you looking for a specific comparison?

Yes, can you compare decision trees and neural networks?

Sure! Decision trees are often easier to interpret and can perform well on smaller datasets, while neural networks excel in complex patterns and larger datasets.

What factors influence their accuracy?

Factors include the quality and size of the dataset, feature selection, model complexity, and the presence of noise in the data.

Which one would you recommend for a classification task?

It depends on your dataset. For smaller, simpler datasets, decision trees might be better. For larger, more complex datasets, neural networks could outperform.