EFFECTIVE RNN BASED FEATURE INTERACTION MODEL USING CLOUD DATABASES

Identification of Feature interaction is the challenging task particularly for high dimensional database in the research field of feature selection which plays a major role in Machine Learning. “Effective RNN based Feature Interaction Model using Cloud Databases” is a Recurrent Neural Network based approach in the Cloud environment which detects positive feature interaction. The proposed RNN based Feature Interaction model consists of Feature Interaction Identifier and Redundant Feature Interaction Remover. The Feature Interaction Identifiers identifies the Feature Interaction pair in the given dataset which is retrieved from Cloud database. The Redundant Feature Interaction Remover removes the duplicate Feature Interaction Pairs which are produced from the Feature Interaction Identifiers and achieves Positive Feature Interaction. The four Medical Databases obtained from AWS Cloud is used to evaluate the performance of the proposed Feature Interaction Model. The experimental and evaluation results obtained on these Cloud databases show that a proposed RNN based Feature Interaction Model performs feature interaction with significant improvement in classification accuracy better than conventional Feature Selection Models.