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Abstract
Prediction technique is one of the strongest subset in the field of Data Mining to find out dynamic patterns or behaviour among the training datasets. The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features. Prediction values are usually continuous when classification values are discrete. Neural Network Analyses, Classification, Regression trees and Decision Trees are major analytic methods for predictive data mining. Decision trees learn from data to approximate a sine curve with a set of if-then-else decision rules. Decision Tree method is one of the non-parametric supervised learning method used for classification and regression. Neural network method is used for classification, clustering, feature mining, prediction and pattern recognition. In more practical terms neural networks are non-linear statistical data modeling tools.