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 ...

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 ...

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

Figuring out what information should be classified and controlling access to it has been an eternal headache for defense and national security organizations—a headache that got a lot of attention ...

How can closely related mental illnesses with similar symptoms be reliably distinguished from one another? As part of a ...

The cotton bollworm, Helicoverpa armigera (Hϋbner) is one of the most important pests affecting crop production globally. The data-mining technique, for predicting pest incidence using biotic and ...

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 ...

Binary Classification Using a scikit Decision Tree Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily ...