A Novel Approach for the Assessment of Decision Stump & Upgraded Rf Classification Algorithms

The classification models in data mining consists of decision tree, neural network, genetic algorithm, rough set, statistical model, etc. In this research, we have proposed and deliberated a new algorithm called Upgraded Random Forest, which is applied for the classification of sensor discrimination dataset. Here we considered for classification of multisource Sensor Discrimination data. The Upgraded RF approach becomes extreme attention for multi-source classification. The methodology which we are developed is not only a nonparametric but it also applies for the assessment and significance of the specific variables in the classification.