Decision Tree: A tree-structured model used for classification and regression in which internal nodes represent tests on attributes and leaf nodes represent outcome labels.

The two main downsides to decision trees are that they often don't work well with large datasets, and they are highly susceptible to model overfitting. When tackling a binary classification problem, ...

Our bivariate genetic algorithm for constructing a decision tree performs very well, scales up quite nicely to handle data sets with hundreds of thousands of points, and requires only a small percent ...

How to Evaluate a Decision Tree Model. A decision tree can help you make tough choices between different paths and outcomes, but only if you evaluate the model correctly. Decision trees are ...

What is a Decision Tree? A decision tree is a visual and logical model used to guide decision-making or make predictions. It breaks down complex problems into a sequence of simpler choices. Each ...

The visual data mining process, seen in the first part of this two-part article, revealed patterns in four dimensions between cumulative gas well production and independent variables ...

But there is also some empirical work comparing various algorithms across many datasets and drawing some conclusions, what types of problems tend to do better with trees vs logistic regression.

Chemotherapy-induced peripheral neuropathy (CIPN) poses a substantial challenge in breast cancer (BC) chemotherapy, affecting the patient's quality of life. Recent studies have focused on exploring ...

Evolutionary algorithms have emerged as a robust alternative to traditional greedy approaches for decision tree induction. By mimicking the natural selection process, these algorithms iterate over ...