ABSTRACT
This chapter describes predictive analytics algorithms and its usage in R/Rattle with illustrative examples. Building model focuses on learning relationships between the input variables and target variable. Data mining model building algorithms are categorized in to descriptive analytics and predictive analytics. The dataset contain students’ details which have been recorded and subjected to the data mining process. During the learning phase, network learns by adjusting weights so as to be able to predict the correct class labels of the input tuples. Classification is one of the powerful techniques in data mining to build models from an input dataset which can be used for predicting students’ academic performance in current end of semester examination. Decision trees are traditional building blocks of data mining. Artificial neural network method is used in the educational field for predicting and classifying students based on their academic performance.
