A new classification tree offers a practical alternative for evaluating esophagogastric junction outflow disorders when more ...

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 ...

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 ...

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 ...

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

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. "Jump ...

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...

Machine learning (ML) opens new opportunities for advancing the classification of traumatic brain injury (TBI). Effectively classifying TBI cases remains a challenge due to the complexity of cognitive ...