Integrating the power of social media dataset impact in medical diagnosis

Technology gives consumer the power to investigate products to label and criticise in equal measure, and more. The emergence of internet-based social media has made it possible for one person to communicate with public about products. Many companies have pages on social networks to complement the information held about products, feedback about products. This paper is discusses about the dataset used in this work for medical diagnosis, experimental scenario and also about obtained result and discussion of the proposed system and reason for achievements on decision making process. The proposed algorithms applied to the dataset from JAVA code and it contains tools for data analysis and predictive modelling. The input dataset of the WEKA are used in the form of CSV file; the performance comparative analysis between the proposed rules-based classifier. The performance of the proposed hybrid behaviour analysis model provides better performance than other individual classifier