Author(s): Sweety R. Patel; Mittal C. Patel; , A. N. Nawathe
Classification is application areas of neural networks. To generate an algorithm to classify multiclass and single class datasets to achieve high diversity and more accuracy. Ensemble Data Mining Methods provides the power of multiple classifiers to achieve better prediction accuracy than any of the individual classifier could on their own. An ensemble approach involves employment of multiple classifiers and combination of their predictions. Artificial Neural networks are very flexible with respect to incomplete, missing and noisy data and also makes the data to use for dynamic environment. Diversity in an ensemble of neural networks can be handled by manipulating either input data or output data. The paper will help the better understanding of different directions in which research of ensembles has been done in field of noisy data collection