Decision tree outperforms logistic regression in complex datasets, improving accuracy.
Classification is a key part of machine learning. Researchers compared logistic regression and decision tree algorithms on different datasets. The results showed that decision trees work better with complex data and slight imbalances, while logistic regression is more accurate with simpler data and balanced distributions.
