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 a ...

BERIL-1: Biomarker results from targeted sequencing of circulating tumor DNA (ctDNA) and archival tissue in a randomized phase II study of buparlisib (BKM120) or placebo plus paclitaxel in patients ...

A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A binary classification problem is one where the goal is to predict the value ...

Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily interpretable, but often don't work well with large ...

Objective: To determine whether classification tree techniques used on survey data collected at enrollment from older adults in a Medicare HMO could predict the likelihood of an individual being in a ...

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 point ...