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 ...

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 ...

This paper presents a general framework based on copulas for modeling dependent multivariate uncertainties through the use of a decision tree. The proposed dependent decision tree model allows ...

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 ...

The two main downsides to decision trees are that they often don't work well with large datasets, and they are highly susceptible to model overfitting. When tackling a binary classification problem, ...

Discordance Between the Initial Diagnosis of Sarcomas and Subsequent Histopathological Revision and Molecular Analyses in a Sarcoma Reference Center in Brazil In this prospective study of 170 patients ...

Malware incidents cost organizations and industries billions of dollars every year. In a 2012 worldwide survey on the financial impacts of malware, more than 2,600 business leaders and IT security ...

Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...