Pattern Classification with Random Decision Forest

Classifier is a fundamental method for data analysis. It is widely used for pattern recognition, feature extraction, image segmentation, function approximation, and data mining. To deal with complicated problem, the ensemble classifier based on Random decision forest method was introduced. It is consists of many decision trees and outputs the class that is the mode of the class´s output by individual trees with each trained in different parameter systems. From the results, it shows that it is an effectively method.