In this paper, we propose a new decision forest algorithm that builds a set of highly accurate
decision trees by exploiting the strength of all non-class attributes available in a data set …

Decision trees are popularly used in a wide range of real world problems for both prediction
and classification (logic) rules discovery. A decision forest is an ensemble of decision trees …

Random Forest is one of the most popular decision forest building algorithms that uses
decision trees as the base classifier. Decision trees for Random Forest are formed from the …

Manufacturing companies sometimes suffer from unexpected production disruptions/
interruptions events (DIEs), affecting the production performance and cost. Since DIEs vary …

Due to its simplicity and good performance, Random Forest attains much interest from the
research community. The splitting attribute at each node of a decision tree for Random …

One of the most important requirements for a decision forest to secure better ensemble
accuracy is generating simultaneously accurate as well as diverse decision trees as base …

Random Forest draws much interest from the research community because of its simplicity
and excellent performance. The splitting attribute at each node of a decision tree for …