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 ...

Discover how random forests, a machine-learning technique, enhance prediction accuracy by combining insights from multiple ...

Several approaches can be taken to predict case membership in the classes of a dependent variable. Classification and regression trees (CART) analysis has been cited repeatedly as a powerful ...

Clinical Relevance of Noncoding Adenosine-to-Inosine RNA Editing in Multiple Human Cancers In total, 60 CDTs were necessary to cover the whole guideline and were driven by 114 data items. Data items ...

This is a preview. Log in through your library . Abstract Objective: Classification tree analysis is a potentially powerful tool for investigating multilevel interactions. Within the context of colon ...

Morbidity After Sentinel Lymph Node Biopsy in Primary Breast Cancer: Results From a Randomized Controlled Trial Data were uniformly collected on 1,433 referred men with a serum prostate-specific ...

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 ...