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 ...

The Data Science Lab 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 ...

The predictive ability of the tree to differentiate survivors and non-survivors was determined by the ROC curve. The classification tree was developed in the program R-2.7.0-WIN.

Classification and regression trees can identify 6-month mortality risk for patients with advanced hepatocellular carcinoma.

There are many techniques that have been developed in data analytics. In this short course, we will focus on classification, or supervised learning techniques. These approaches include linear ...

Wilfried Thuiller, , Sandra Lavorel, Generalized Models vs. Classification Tree Analysis: Predicting Spatial Distributions of Plant Species at Different Scales ...

Classification and Regression Trees (CART) Course Topics Classification and regression tree (CART) methods are a class of data mining techniques which constitute an alternative approach to classical ...

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

A non-specific hip pain classification tree had a mean (SE) sensitivity and specificity of 0.78 (0.058) and 0.28 (0.080). Conclusions Patients with LHP in the absence of difficulty with manipulating ...