Missing Value Treatment using Effective Optimization on Data from Multiple Social Media

Missing value are broad in numerous genuine applications. Missing value imputation and in addition treatment is vital on the grounds that the skipping of missing value based records can harm the general results. For instance, if the client conclusions about information leak in India are fetched from social media then the client having hidden personal information can be covered in missing records. Such records cannot be skipped because of the privacy concerns of the users and therefore missing value imputation should be implemented on such records. In this research work, random forest approach for missing value imputation is devised and implemented on the different types of social media like youtube, twitter, tumblr.